tn.plot()
<matplotlib.axes._subplots.AxesSubplot at 0x2733f65bf28>
(ddcmap.groupby('county')['classroom_teacher','principal'].median()).reset_index()
| county | classroom_teacher | principal | |
|---|---|---|---|
| 0 | Anderson | 46386.0 | 81234.0 |
| 1 | Bedford | 45733.0 | 78245.0 |
| 2 | Benton | 45908.0 | 64938.0 |
| 3 | Bledsoe | 48781.0 | 69205.0 |
| 4 | Blount | 61790.0 | 99120.0 |
| 5 | Bradley | 51357.0 | 86421.5 |
| 6 | Campbell | 45726.0 | 72243.0 |
| 7 | Cannon | 44245.0 | 68512.0 |
| 8 | Carroll | 45071.0 | 67514.5 |
| 9 | Carter | 46066.5 | 70638.5 |
| 10 | Cheatham | 45380.0 | 78234.0 |
| 11 | Chester | 45955.0 | 76149.0 |
| 12 | Claiborne | 43714.0 | 72503.0 |
| 13 | Clay | 43905.0 | 62520.0 |
| 14 | Cocke | 46372.5 | 75449.5 |
| 15 | Coffee | 50964.0 | 75321.0 |
| 16 | Crockett | 45012.0 | 66842.0 |
| 17 | Cumberland | 42485.0 | 73569.0 |
| 18 | Davidson | 51855.0 | 103445.0 |
| 19 | Decatur | 45987.0 | 73763.0 |
| 20 | Dekalb | 43183.0 | 67396.0 |
| 21 | Dickson | 44708.0 | 73545.0 |
| 22 | Dyer | 50130.5 | 82861.5 |
| 23 | Fayette | 41855.0 | 61612.0 |
| 24 | Fentress | 42922.0 | 63072.0 |
| 25 | Franklin | 46957.0 | 72442.0 |
| 26 | Gibson | 44757.0 | 76023.0 |
| 27 | Giles | 46535.0 | 75975.0 |
| 28 | Grainger | 45831.0 | 68502.0 |
| 29 | Greene | 49081.5 | 81274.5 |
| 30 | Grundy | 42582.0 | 63014.0 |
| 31 | Hamblen | 49134.0 | 83650.0 |
| 32 | Hamilton | 50469.0 | 90784.0 |
| 33 | Hancock | 41992.0 | 66948.0 |
| 34 | Hardeman | 46467.0 | 72536.0 |
| 35 | Hardin | 44760.0 | 63897.0 |
| 36 | Hawkins | 46499.5 | 72565.0 |
| 37 | Haywood | 44304.0 | 68504.0 |
| 38 | Henderson | 46787.0 | 70447.0 |
| 39 | Henry | 49238.0 | 81162.0 |
| 40 | Hickman | 44293.0 | 77659.0 |
| 41 | Houston | 47025.0 | 67201.0 |
| 42 | Humphreys | 46159.0 | 69350.0 |
| 43 | Jackson | 44936.0 | 68643.0 |
| 44 | Jefferson | 45711.0 | 75567.0 |
| 45 | Johnson | 44491.0 | 67080.0 |
| 46 | Knox | 49384.0 | 95880.0 |
| 47 | Lake | 42329.0 | 69334.0 |
| 48 | Lauderdale | 44842.0 | 78089.0 |
| 49 | Lawrence | 47480.0 | 73242.0 |
| 50 | Lewis | 47369.0 | 77934.5 |
| 51 | Lincoln | 48529.0 | 85181.0 |
| 52 | Loudon | 50248.0 | 86751.5 |
| 53 | Macon | 45804.0 | 74033.0 |
| 54 | Madison | 48908.0 | 84961.0 |
| 55 | Marion | 43847.5 | 65142.0 |
| 56 | Marshall | 48272.0 | 77559.0 |
| 57 | Maury | 47787.0 | 88736.0 |
| 58 | Mcminn | 49123.0 | 83138.0 |
| 59 | Mcnairy | 44326.0 | 72410.0 |
| 60 | Meigs | 49633.0 | 72803.0 |
| 61 | Monroe | 47785.0 | 70007.0 |
| 62 | Montgomery | 52503.0 | 95957.0 |
| 63 | Moore | 46992.0 | 73340.0 |
| 64 | Morgan | 44223.0 | 72545.0 |
| 65 | Obion | 47327.0 | 79783.0 |
| 66 | Overton | 42734.0 | 63263.0 |
| 67 | Perry | 45979.0 | 67719.0 |
| 68 | Pickett | 46202.0 | 65663.0 |
| 69 | Polk | 48429.0 | 77124.0 |
| 70 | Putnam | 47186.0 | 74008.0 |
| 71 | Rhea | 46051.0 | 69004.0 |
| 72 | Roane | 50470.0 | 78674.0 |
| 73 | Robertson | 44548.0 | 74412.0 |
| 74 | Rutherford | 51697.0 | 90088.5 |
| 75 | Scott | 44043.5 | 69429.0 |
| 76 | Sequatchie | 46463.0 | 73347.0 |
| 77 | Sevier | 50356.0 | 91611.0 |
| 78 | Shelby | 57769.0 | 106055.0 |
| 79 | Smith | 42951.0 | 64385.0 |
| 80 | Stewart | 47148.0 | 70787.0 |
| 81 | Sullivan | 52591.0 | 94810.0 |
| 82 | Sumner | 46988.0 | 85660.0 |
| 83 | Tipton | 51528.0 | 81081.0 |
| 84 | Trousdale | 44706.0 | 72809.0 |
| 85 | Unicoi | 44148.0 | 65544.0 |
| 86 | Union | 43970.0 | 69540.0 |
| 87 | Van buren | 46806.0 | 63002.0 |
| 88 | Warren | 45881.0 | 72458.0 |
| 89 | Washington | 52529.0 | 82704.5 |
| 90 | Wayne | 46135.0 | 70226.0 |
| 91 | Weakley | 44837.0 | 74995.0 |
| 92 | White | 48576.0 | 66789.0 |
| 93 | Williamson | 54144.5 | 109897.0 |
| 94 | Wilson | 50751.5 | 91379.5 |
freq = pct_man.pct
plt.hist(freq)
plt.ylabel('Frequency of Chronic Absenteeism Amongst TN Counties')
plt.show()
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-358-674da8add515> in <module>() 1 freq = pct_man.pct 2 plt.hist(freq) ----> 3 plt.ylabel('Frequency of Chronic Absenteeism Amongst TN Counties') 4 plt.show() TypeError: 'str' object is not callable
plt.boxplot(freq)
ax.set_xlabel('Percentage of Chronically Absent Students')
Text(0.5,325.804,'Percentage of Chronically Absent Students')
tn_abs1=pd.merge(group_co,tn,how = 'outer', left_on='county', right_on='NAME10')
tn_abs1.shape
tn_abs2=pd.merge(tn_abs1,pct_man, left_on = 'NAME10', right_on='county' )
(tn_abs2['pct']*100).round() == tn_abs2['pct_chronically_absent'].round() # Spoke with Mary... using calculated pct may be more accurate
0 False 1 True 2 True 3 True 4 False 5 True 6 True 7 False 8 False 9 False 10 True 11 True 12 True 13 True 14 False 15 False 16 True 17 True 18 True 19 True 20 True 21 True 22 False 23 True 24 False 25 True 26 False 27 True 28 True 29 False 30 True 31 True 32 True 33 True 34 True 35 True 36 True 37 True 38 False 39 False 40 True 41 True 42 True 43 True 44 True 45 True 46 True 47 True 48 True 49 True 50 True 51 False 52 False 53 True 54 True 55 False 56 True 57 True 58 False 59 False 60 True 61 False 62 False 63 True 64 True 65 False 66 True 67 True 68 True 69 True 70 True 71 False 72 True 73 True 74 False 75 False 76 True 77 True 78 False 79 True 80 True 81 False 82 False 83 True 84 True 85 True 86 True 87 True 88 True 89 True 90 True 91 True 92 True 93 True 94 False dtype: bool
tn_abs2
| pct_chronically_absent | STATEFP10 | COUNTYFP10 | COUNTYNS10 | GEOID10 | NAME10 | NAMELSAD10 | LSAD10 | CLASSFP10 | MTFCC10 | CSAFP10 | CBSAFP10 | METDIVFP10 | FUNCSTAT10 | ALAND10 | AWATER10 | INTPTLAT10 | INTPTLON10 | geometry | n_students | n_chronically_absent | pct | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 11.066667 | 47 | 001 | 01639722 | 47001 | Anderson | Anderson County | 06 | H1 | G4020 | 314 | 28940 | None | A | 873245292 | 19771988 | +36.1167307 | -084.1954177 | POLYGON ((-84.33464599999999 36.0302, -84.3346... | 11621 | 1432 | 0.123225 |
| 1 | 12.800000 | 47 | 003 | 01639723 | 47003 | Bedford | Bedford County | 06 | H1 | G4020 | None | 43180 | None | A | 1226710123 | 2983154 | +35.5136604 | -086.4582939 | POLYGON ((-86.499674 35.359984, -86.499798 35.... | 8502 | 1088 | 0.127970 |
| 2 | 9.000000 | 47 | 005 | 01639724 | 47005 | Benton | Benton County | 06 | H1 | G4020 | None | None | None | A | 1020822586 | 109009079 | +36.0692530 | -088.0712118 | POLYGON ((-87.95178799999999 36.225321, -87.95... | 2123 | 192 | 0.090438 |
| 3 | 16.600000 | 47 | 007 | 01639725 | 47007 | Bledsoe | Bledsoe County | 06 | H1 | G4020 | None | None | None | A | 1052635810 | 838365 | +35.5936682 | -085.2059790 | POLYGON ((-85.277034 35.390432, -85.277891 35.... | 1681 | 279 | 0.165973 |
| 4 | 7.100000 | 47 | 009 | 01639726 | 47009 | Blount | Blount County | 06 | H1 | G4020 | 314 | 28940 | None | A | 1447041818 | 20307831 | +35.6881849 | -083.9229731 | POLYGON ((-84.14251999999999 35.796954, -84.14... | 17779 | 1338 | 0.075257 |
| 5 | 11.100000 | 47 | 011 | 01639727 | 47011 | Bradley | Bradley County | 06 | H1 | G4020 | 174 | 17420 | None | A | 851489045 | 6959355 | +35.1539144 | -084.8594137 | POLYGON ((-85.008478 35.09269, -85.00911099999... | 15269 | 1704 | 0.111599 |
| 6 | 21.600000 | 47 | 013 | 01639728 | 47013 | Campbell | Campbell County | 06 | H1 | G4020 | 314 | 29220 | None | A | 1243689525 | 46503453 | +36.4015922 | -084.1592495 | POLYGON ((-84.323469 36.395527, -84.3243509999... | 5456 | 1178 | 0.215909 |
| 7 | 14.500000 | 47 | 015 | 01648572 | 47015 | Cannon | Cannon County | 06 | H1 | G4020 | 400 | 34980 | None | A | 687991703 | 156872 | +35.8083940 | -086.0624044 | POLYGON ((-85.890631 35.852794, -85.8906909999... | 1894 | 275 | 0.145195 |
| 8 | 6.833333 | 47 | 017 | 01639729 | 47017 | Carroll | Carroll County | 06 | H1 | G4020 | None | None | None | A | 1552055889 | 2144122 | +35.9678963 | -088.4516591 | POLYGON ((-88.43844199999999 36.149538, -88.43... | 4519 | 340 | 0.075238 |
| 9 | 19.050000 | 47 | 019 | 01639730 | 47019 | Carter | Carter County | 06 | H1 | G4020 | 304 | 27740 | None | A | 883711484 | 16656931 | +36.2847441 | -082.1265932 | POLYGON ((-82.05894599999999 36.367415, -82.05... | 7681 | 1686 | 0.219503 |
| 10 | 14.100000 | 47 | 021 | 01639731 | 47021 | Cheatham | Cheatham County | 06 | H1 | G4020 | 400 | 34980 | None | A | 783308267 | 11964151 | +36.2551800 | -087.1008163 | POLYGON ((-87.148602 36.422773, -87.1486709999... | 6232 | 881 | 0.141367 |
| 11 | 16.000000 | 47 | 023 | 01639732 | 47023 | Chester | Chester County | 06 | H1 | G4020 | 297 | 27180 | None | A | 740052043 | 575590 | +35.4166392 | -088.6055046 | POLYGON ((-88.761264 35.451615, -88.7605559999... | 2846 | 454 | 0.159522 |
| 12 | 22.900000 | 47 | 025 | 01639733 | 47025 | Claiborne | Claiborne County | 06 | H1 | G4020 | None | None | None | A | 1125555951 | 18116086 | +36.5015565 | -083.6607235 | POLYGON ((-83.690709 36.360281, -83.691109 36.... | 4219 | 967 | 0.229201 |
| 13 | 9.000000 | 47 | 027 | 01648573 | 47027 | Clay | Clay County | 06 | H1 | G4020 | None | None | None | A | 612626617 | 59071040 | +36.5457651 | -085.5457178 | POLYGON ((-85.707937 36.52198, -85.70795699999... | 1026 | 92 | 0.089669 |
| 14 | 15.100000 | 47 | 029 | 01639734 | 47029 | Cocke | Cocke County | 06 | H1 | G4020 | 314 | 35460 | None | A | 1125518964 | 22196995 | +35.9161984 | -083.1192234 | POLYGON ((-83.304716 35.89886, -83.30416799999... | 5127 | 866 | 0.168910 |
| 15 | 12.366667 | 47 | 031 | 01639735 | 47031 | Coffee | Coffee County | 06 | H1 | G4020 | None | 46100 | None | A | 1110993322 | 14496456 | +35.4887586 | -086.0782188 | POLYGON ((-86.02704 35.343837, -86.02796599999... | 9013 | 1138 | 0.126262 |
| 16 | 4.933333 | 47 | 033 | 01648574 | 47033 | Crockett | Crockett County | 06 | H1 | G4020 | None | None | None | A | 687731312 | 529234 | +35.8113116 | -089.1353494 | POLYGON ((-89.08743699999999 35.694999, -89.08... | 2899 | 136 | 0.046913 |
| 17 | 12.300000 | 47 | 035 | 01639736 | 47035 | Cumberland | Cumberland County | 06 | H1 | G4020 | None | 18900 | None | A | 1763847584 | 9825917 | +35.9523984 | -084.9947614 | POLYGON ((-84.96183099999999 36.15048, -84.961... | 7172 | 883 | 0.123118 |
| 18 | 16.900000 | 47 | 037 | 01639737 | 47037 | Davidson | Davidson County | 06 | H6 | G4020 | 400 | 34980 | None | C | 1305438546 | 56749226 | +36.1691287 | -086.7847898 | (POLYGON ((-86.52152799999999 36.138464, -86.5... | 82312 | 13931 | 0.169246 |
| 19 | 19.600000 | 47 | 039 | 01639739 | 47039 | Decatur | Decatur County | 06 | H1 | G4020 | None | None | None | A | 864654041 | 28588845 | +35.6034221 | -088.1073838 | POLYGON ((-88.035213 35.616679, -88.035144 35.... | 1569 | 307 | 0.195666 |
| 20 | 10.900000 | 47 | 041 | 01639738 | 47041 | Dekalb | DeKalb County | 06 | H1 | G4020 | None | None | None | A | 788253896 | 63816416 | +35.9822204 | -085.8335963 | POLYGON ((-85.76769499999999 36.072922, -85.76... | 2870 | 313 | 0.109059 |
| 21 | 10.800000 | 47 | 043 | 01639740 | 47043 | Dickson | Dickson County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1268824458 | 3688818 | +36.1455325 | -087.3641546 | (POLYGON ((-87.15239799999999 36.288627, -87.1... | 8256 | 894 | 0.108285 |
| 22 | 9.750000 | 47 | 045 | 01639741 | 47045 | Dyer | Dyer County | 06 | H1 | G4020 | None | 20540 | None | A | 1326920403 | 36780572 | +36.0541962 | -089.3983056 | POLYGON ((-89.49092499999999 35.947723, -89.49... | 6334 | 592 | 0.093464 |
| 23 | 13.500000 | 47 | 047 | 01639742 | 47047 | Fayette | Fayette County | 06 | H1 | G4020 | None | 32820 | None | A | 1825386659 | 3762451 | +35.1969933 | -089.4138027 | POLYGON ((-89.46137399999999 34.993857, -89.46... | 3282 | 444 | 0.135283 |
| 24 | 13.650000 | 47 | 049 | 01639743 | 47049 | Fentress | Fentress County | 06 | H1 | G4020 | None | None | None | A | 1291399079 | 829338 | +36.3760785 | -084.9327026 | POLYGON ((-84.73159799999999 36.350655, -84.73... | 2652 | 347 | 0.130845 |
| 25 | 14.400000 | 47 | 051 | 01639744 | 47051 | Franklin | Franklin County | 06 | H1 | G4020 | None | 46100 | None | A | 1436257485 | 54890094 | +35.1559259 | -086.0992032 | POLYGON ((-86.15281399999999 34.989926, -86.15... | 5309 | 764 | 0.143907 |
| 26 | 9.880000 | 47 | 053 | 01639745 | 47053 | Gibson | Gibson County | 06 | H1 | G4020 | 297 | 26480 | None | A | 1561094821 | 2353199 | +35.9916941 | -088.9337756 | POLYGON ((-88.88752199999999 35.796335, -88.88... | 8757 | 769 | 0.087815 |
| 27 | 10.600000 | 47 | 055 | 01639746 | 47055 | Giles | Giles County | 06 | H1 | G4020 | None | None | None | A | 1582292854 | 642569 | +35.2027228 | -087.0353190 | POLYGON ((-87.089895 34.99659, -87.09147899999... | 3799 | 401 | 0.105554 |
| 28 | 36.200000 | 47 | 057 | 01648575 | 47057 | Grainger | Grainger County | 06 | H1 | G4020 | 314 | 34100 | None | A | 726751601 | 56614954 | +36.2774634 | -083.5094926 | POLYGON ((-83.381502 36.265431, -83.3817969999... | 3376 | 1223 | 0.362263 |
| 29 | 8.450000 | 47 | 059 | 01639747 | 47059 | Greene | Greene County | 06 | H1 | G4020 | None | 24620 | None | A | 1611399661 | 5056718 | +36.1789979 | -082.8477460 | POLYGON ((-82.954104 35.997399, -82.954399 35.... | 9606 | 883 | 0.091922 |
| 30 | 11.900000 | 47 | 061 | 01639748 | 47061 | Grundy | Grundy County | 06 | H1 | G4020 | None | None | None | A | 933778866 | 1522451 | +35.3872730 | -085.7221882 | POLYGON ((-85.88787599999999 35.249037, -85.88... | 2046 | 243 | 0.118768 |
| 31 | 6.700000 | 47 | 063 | 01648576 | 47063 | Hamblen | Hamblen County | 06 | H1 | G4020 | 314 | 34100 | None | A | 417450989 | 37877929 | +36.2183967 | -083.2660711 | POLYGON ((-83.234191 36.281792, -83.2336909999... | 10161 | 677 | 0.066627 |
| 32 | 8.900000 | 47 | 065 | 01639749 | 47065 | Hamilton | Hamilton County | 06 | H1 | G4020 | 174 | 16860 | None | A | 1404890184 | 86631783 | +35.1591860 | -085.2022955 | POLYGON ((-85.17522699999999 34.985976, -85.17... | 43443 | 3859 | 0.088829 |
| 33 | 16.500000 | 47 | 067 | 01648577 | 47067 | Hancock | Hancock County | 06 | H1 | G4020 | None | None | None | A | 575858117 | 2984311 | +36.5214195 | -083.2274526 | POLYGON ((-83.101524 36.594039, -83.101517 36.... | 972 | 160 | 0.164609 |
| 34 | 13.400000 | 47 | 069 | 01639750 | 47069 | Hardeman | Hardeman County | 06 | H1 | G4020 | None | None | None | A | 1729510170 | 6768412 | +35.2181307 | -088.9890374 | POLYGON ((-89.108599 35.431897, -89.108054 35.... | 3522 | 473 | 0.134299 |
| 35 | 15.800000 | 47 | 071 | 01639751 | 47071 | Hardin | Hardin County | 06 | H1 | G4020 | None | None | None | A | 1495246952 | 49148746 | +35.2018926 | -088.1856958 | POLYGON ((-88.196462 35.379561, -88.196457 35.... | 3433 | 541 | 0.157588 |
| 36 | 14.350000 | 47 | 073 | 01639752 | 47073 | Hawkins | Hawkins County | 06 | H1 | G4020 | 304 | 28700 | None | A | 1261259454 | 32691660 | +36.4522060 | -082.9313857 | POLYGON ((-82.942691 36.546294, -82.9420229999... | 7328 | 1015 | 0.138510 |
| 37 | 9.700000 | 47 | 075 | 01639753 | 47075 | Haywood | Haywood County | 06 | H1 | G4020 | None | 15140 | None | A | 1380753077 | 2457129 | +35.5866898 | -089.2825359 | POLYGON ((-89.46887699999999 35.619034, -89.46... | 2821 | 273 | 0.096774 |
| 38 | 12.100000 | 47 | 077 | 01639754 | 47077 | Henderson | Henderson County | 06 | H1 | G4020 | None | None | None | A | 1346982937 | 15049181 | +35.6539945 | -088.3876741 | POLYGON ((-88.441276 35.490306, -88.441349 35.... | 4689 | 610 | 0.130092 |
| 39 | 10.600000 | 47 | 079 | 01639755 | 47079 | Henry | Henry County | 06 | H1 | G4020 | None | 37540 | None | A | 1455823082 | 81118140 | +36.3253983 | -088.3003844 | POLYGON ((-88.52524699999999 36.258424, -88.52... | 4565 | 478 | 0.104710 |
| 40 | 13.100000 | 47 | 081 | 01639756 | 47081 | Hickman | Hickman County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1586365395 | 332916 | +35.8023956 | -087.4671144 | POLYGON ((-87.43504299999999 35.982596, -87.43... | 3272 | 430 | 0.131418 |
| 41 | 39.400000 | 47 | 083 | 01648578 | 47083 | Houston | Houston County | 06 | H1 | G4020 | None | None | None | A | 518739541 | 17322109 | +36.2857772 | -087.7056048 | POLYGON ((-87.79108599999999 36.244559, -87.79... | 1329 | 523 | 0.393529 |
| 42 | 14.400000 | 47 | 085 | 01639757 | 47085 | Humphreys | Humphreys County | 06 | H1 | G4020 | None | None | None | A | 1375232049 | 66620771 | +36.0404396 | -087.7906251 | POLYGON ((-87.707509 36.227205, -87.7074119999... | 2842 | 410 | 0.144265 |
| 43 | 9.900000 | 47 | 087 | 01639758 | 47087 | Jackson | Jackson County | 06 | H1 | G4020 | None | 18260 | None | A | 798545703 | 29019623 | +36.3542420 | -085.6741819 | POLYGON ((-85.60680599999999 36.479111, -85.60... | 1444 | 143 | 0.099030 |
| 44 | 13.200000 | 47 | 089 | 01639759 | 47089 | Jefferson | Jefferson County | 06 | H1 | G4020 | 314 | 34100 | None | A | 709858548 | 104186904 | +36.0484787 | -083.4409664 | POLYGON ((-83.490697 36.166588, -83.489797 36.... | 7105 | 938 | 0.132020 |
| 45 | 8.700000 | 47 | 091 | 01639760 | 47091 | Johnson | Johnson County | 06 | H1 | G4020 | None | None | None | A | 773046157 | 11001626 | +36.4532035 | -081.8612367 | POLYGON ((-81.993505 36.433888, -81.993904 36.... | 1984 | 173 | 0.087198 |
| 46 | 14.900000 | 47 | 093 | 01639761 | 47093 | Knox | Knox County | 06 | H1 | G4020 | 314 | 28940 | None | A | 1316271254 | 45715161 | +35.9927265 | -083.9377209 | POLYGON ((-84.072906 36.049719, -84.0730239999... | 58691 | 8767 | 0.149376 |
| 47 | 19.900000 | 47 | 095 | 01639762 | 47095 | Lake | Lake County | 06 | H1 | G4020 | None | None | None | A | 429379130 | 72802129 | +36.3339054 | -089.4855365 | POLYGON ((-89.537183 36.274385, -89.5376749999... | 772 | 154 | 0.199482 |
| 48 | 9.800000 | 47 | 097 | 01639763 | 47097 | Lauderdale | Lauderdale County | 06 | H1 | G4020 | None | None | None | A | 1222453808 | 92173871 | +35.7629507 | -089.6277318 | POLYGON ((-89.57808899999999 35.925089, -89.57... | 4045 | 398 | 0.098393 |
| 49 | 8.300000 | 47 | 099 | 01639764 | 47099 | Lawrence | Lawrence County | 06 | H1 | G4020 | None | 29980 | None | A | 1598355330 | 2229584 | +35.2204764 | -087.3965460 | POLYGON ((-87.437074 35.002776, -87.438316 35.... | 6653 | 554 | 0.083271 |
| 50 | 11.000000 | 47 | 101 | 01639765 | 47101 | Lewis | Lewis County | 06 | H1 | G4020 | None | None | None | A | 730608109 | 1031587 | +35.5232441 | -087.4969827 | POLYGON ((-87.32755399999999 35.5686, -87.3275... | 3024 | 331 | 0.109458 |
| 51 | 13.500000 | 47 | 103 | 01639766 | 47103 | Lincoln | Lincoln County | 06 | H1 | G4020 | None | None | None | A | 1477169515 | 990366 | +35.1425322 | -086.5933882 | POLYGON ((-86.83367799999999 35.082324, -86.83... | 3767 | 507 | 0.134590 |
| 52 | 13.100000 | 47 | 105 | 01639767 | 47105 | Loudon | Loudon County | 06 | H1 | G4020 | 314 | 28940 | None | A | 593665426 | 47019542 | +35.7374500 | -084.3162040 | (POLYGON ((-84.539963 35.670465, -84.540218999... | 6869 | 818 | 0.119086 |
| 53 | 10.800000 | 47 | 111 | 01639768 | 47111 | Macon | Macon County | 06 | H1 | G4020 | 400 | 34980 | None | A | 795498380 | 246691 | +36.5378383 | -086.0012306 | POLYGON ((-85.94728099999999 36.420861, -85.94... | 3828 | 415 | 0.108412 |
| 54 | 21.500000 | 47 | 113 | 01639769 | 47113 | Madison | Madison County | 06 | H1 | G4020 | 297 | 27180 | None | A | 1442926509 | 3908964 | +35.6060563 | -088.8334238 | POLYGON ((-88.787847 35.793249, -88.7868259999... | 12480 | 2688 | 0.215385 |
| 55 | 24.500000 | 47 | 115 | 01639770 | 47115 | Marion | Marion County | 06 | H1 | G4020 | 174 | 16860 | None | A | 1290227262 | 36501967 | +35.1334215 | -085.6183990 | POLYGON ((-85.55271399999999 34.983996, -85.55... | 4245 | 828 | 0.195053 |
| 56 | 15.300000 | 47 | 117 | 01639771 | 47117 | Marshall | Marshall County | 06 | H1 | G4020 | None | 30280 | None | A | 972437127 | 1801806 | +35.4683866 | -086.7658862 | POLYGON ((-86.790753 35.703708, -86.7892689999... | 5341 | 818 | 0.153155 |
| 57 | 12.600000 | 47 | 119 | 01639772 | 47119 | Maury | Maury County | 06 | H1 | G4020 | 400 | 17940 | None | A | 1588021250 | 6319194 | +35.6156963 | -087.0777632 | POLYGON ((-87.160281 35.435369, -87.1636839999... | 12228 | 1535 | 0.125532 |
| 58 | 13.200000 | 47 | 107 | 01639773 | 47107 | Mcminn | McMinn County | 06 | H1 | G4020 | 174 | 11940 | None | A | 1114018337 | 5331264 | +35.4244708 | -084.6199625 | POLYGON ((-84.736514 35.516316, -84.7355879999... | 7416 | 1025 | 0.138215 |
| 59 | 9.500000 | 47 | 109 | 01639774 | 47109 | Mcnairy | McNairy County | 06 | H1 | G4020 | None | None | None | A | 1457801922 | 1947871 | +35.1756263 | -088.5646713 | POLYGON ((-88.716481 35.256343, -88.7164739999... | 4124 | 390 | 0.094568 |
| 60 | 12.000000 | 47 | 121 | 01639775 | 47121 | Meigs | Meigs County | 06 | H1 | G4020 | None | None | None | A | 505362806 | 56013385 | +35.5033973 | -084.8238876 | POLYGON ((-84.81092199999999 35.436491, -84.81... | 1663 | 199 | 0.119663 |
| 61 | 14.250000 | 47 | 123 | 01639776 | 47123 | Monroe | Monroe County | 06 | H1 | G4020 | None | None | None | A | 1646104693 | 44013070 | +35.4476659 | -084.2497859 | POLYGON ((-84.450047 35.472714, -84.4512189999... | 6787 | 1011 | 0.148961 |
| 62 | 8.500000 | 47 | 125 | 01639777 | 47125 | Montgomery | Montgomery County | 06 | H1 | G4020 | None | 17300 | None | A | 1396461566 | 12050596 | +36.5003535 | -087.3808865 | POLYGON ((-87.564016 36.339567, -87.564296 36.... | 33026 | 2819 | 0.085357 |
| 63 | 13.600000 | 47 | 127 | 01648579 | 47127 | Moore | Moore County | 06 | H6 | G4020 | None | 46100 | None | C | 334684959 | 3093426 | +35.2888885 | -086.3586840 | POLYGON ((-86.444197 35.277975, -86.4441159999... | 839 | 114 | 0.135876 |
| 64 | 8.800000 | 47 | 129 | 01639778 | 47129 | Morgan | Morgan County | 06 | H1 | G4020 | None | None | None | A | 1352440400 | 809723 | +36.1386970 | -084.6392616 | POLYGON ((-84.42549099999999 36.123657, -84.42... | 2981 | 261 | 0.087555 |
| 65 | 12.250000 | 47 | 131 | 01639779 | 47131 | Obion | Obion County | 06 | H1 | G4020 | 542 | 46460 | None | A | 1410839429 | 27916074 | +36.3581749 | -089.1501746 | POLYGON ((-89.256345 36.506316, -89.250058 36.... | 4909 | 657 | 0.133836 |
| 66 | 11.000000 | 47 | 133 | 01639780 | 47133 | Overton | Overton County | 06 | H1 | G4020 | None | 18260 | None | A | 1122714642 | 3500016 | +36.3448504 | -085.2830756 | POLYGON ((-85.326746 36.2009, -85.326901999999... | 3014 | 333 | 0.110484 |
| 67 | 11.000000 | 47 | 135 | 01639781 | 47135 | Perry | Perry County | 06 | H1 | G4020 | None | None | None | A | 1074148474 | 21084076 | +35.6597850 | -087.8770272 | POLYGON ((-87.981763 35.774973, -87.9817 35.77... | 1039 | 114 | 0.109721 |
| 68 | 15.600000 | 47 | 137 | 01648580 | 47137 | Pickett | Pickett County | 06 | H1 | G4020 | None | None | None | A | 422113383 | 29822854 | +36.5593638 | -085.0757410 | POLYGON ((-85.17018 36.62484, -85.168763 36.62... | 693 | 108 | 0.155844 |
| 69 | 14.700000 | 47 | 139 | 01639782 | 47139 | Polk | Polk County | 06 | H1 | G4020 | 174 | 17420 | None | A | 1125806416 | 19834205 | +35.1094371 | -084.5411124 | POLYGON ((-84.490274 35.283502, -84.488781 35.... | 2299 | 338 | 0.147020 |
| 70 | 10.000000 | 47 | 141 | 01639783 | 47141 | Putnam | Putnam County | 06 | H1 | G4020 | None | 18260 | None | A | 1038852585 | 3784351 | +36.1408072 | -085.4969279 | POLYGON ((-85.39535599999999 36.055085, -85.39... | 10948 | 1098 | 0.100292 |
| 71 | 11.600000 | 47 | 143 | 01639784 | 47143 | Rhea | Rhea County | 06 | H1 | G4020 | None | None | None | A | 816822960 | 54463425 | +35.6005870 | -084.9495522 | POLYGON ((-85.087121 35.587647, -85.086478 35.... | 5089 | 712 | 0.139910 |
| 72 | 13.000000 | 47 | 145 | 01639785 | 47145 | Roane | Roane County | 06 | H1 | G4020 | 314 | 25340 | None | A | 934229744 | 88755772 | +35.8474721 | -084.5238612 | POLYGON ((-84.620887 35.932199, -84.620812 35.... | 6517 | 846 | 0.129814 |
| 73 | 7.400000 | 47 | 147 | 01639786 | 47147 | Robertson | Robertson County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1233577495 | 451694 | +36.5275304 | -086.8693774 | POLYGON ((-87.073559 36.427653, -87.07508 36.4... | 11149 | 828 | 0.074267 |
| 74 | 8.700000 | 47 | 149 | 01639787 | 47149 | Rutherford | Rutherford County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1604145428 | 12143221 | +35.8433688 | -086.4172127 | POLYGON ((-86.607743 35.981573, -86.6077279999... | 51769 | 5237 | 0.101161 |
| 75 | 8.650000 | 47 | 151 | 01639788 | 47151 | Scott | Scott County | 06 | H1 | G4020 | None | None | None | A | 1378642788 | 2414259 | +36.4372392 | -084.4983861 | POLYGON ((-84.520921 36.596423, -84.501395 36.... | 3965 | 301 | 0.075914 |
| 76 | 19.200000 | 47 | 153 | 01652643 | 47153 | Sequatchie | Sequatchie County | 06 | H1 | G4020 | 174 | 16860 | None | A | 688567749 | 481448 | +35.3723348 | -085.4103438 | POLYGON ((-85.44302599999999 35.26185, -85.443... | 2204 | 424 | 0.192377 |
| 77 | 20.600000 | 47 | 155 | 01639789 | 47155 | Sevier | Sevier County | 06 | H1 | G4020 | 314 | 42940 | None | A | 1534567408 | 13514945 | +35.7912836 | -083.5219545 | POLYGON ((-83.784379 35.876163, -83.7843819999... | 14373 | 2956 | 0.205663 |
| 78 | 8.500000 | 47 | 157 | 01639790 | 47157 | Shelby | Shelby County | 06 | H1 | G4020 | None | 32820 | None | A | 1976612450 | 56576401 | +35.1837942 | -089.8953970 | POLYGON ((-90.137647 34.994714, -90.1376509999... | 137300 | 20038 | 0.145943 |
| 79 | 5.000000 | 47 | 159 | 01639791 | 47159 | Smith | Smith County | 06 | H1 | G4020 | 400 | 34980 | None | A | 814004493 | 28706391 | +36.2556502 | -085.9420775 | POLYGON ((-86.095461 36.34193399999999, -86.09... | 2991 | 150 | 0.050150 |
| 80 | 15.100000 | 47 | 161 | 01639792 | 47161 | Stewart | Stewart County | 06 | H1 | G4020 | None | 17300 | None | A | 1189659929 | 87232255 | +36.5117556 | -087.8515483 | POLYGON ((-87.84630899999999 36.328947, -87.84... | 1983 | 300 | 0.151286 |
| 81 | 14.466667 | 47 | 163 | 01639793 | 47163 | Sullivan | Sullivan County | 06 | H1 | G4020 | 304 | 28700 | None | A | 1070605281 | 42330294 | +36.5102123 | -082.2993965 | POLYGON ((-82.51727099999999 36.595391, -82.51... | 20940 | 3163 | 0.151051 |
| 82 | 9.500000 | 47 | 165 | 01639794 | 47165 | Sumner | Sumner County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1371267673 | 35658276 | +36.4700152 | -086.4585173 | POLYGON ((-86.68059799999999 36.315954, -86.68... | 28914 | 2739 | 0.094729 |
| 83 | 9.700000 | 47 | 167 | 01639795 | 47167 | Tipton | Tipton County | 06 | H1 | G4020 | None | 32820 | None | A | 1187161824 | 38714600 | +35.5002966 | -089.7637081 | (POLYGON ((-90.06520999999999 35.418215, -90.0... | 10749 | 1048 | 0.097497 |
| 84 | 10.200000 | 47 | 169 | 01648581 | 47169 | Trousdale | Trousdale County | 06 | H6 | G4020 | 400 | 34980 | None | C | 295758787 | 6345335 | +36.3930297 | -086.1566909 | POLYGON ((-86.230096 36.349172, -86.235117 36.... | 1259 | 129 | 0.102462 |
| 85 | 20.800000 | 47 | 171 | 01648582 | 47171 | Unicoi | Unicoi County | 06 | H1 | G4020 | 304 | 27740 | None | A | 482165202 | 850686 | +36.1002148 | -082.4182453 | POLYGON ((-82.32576399999999 36.119001, -82.32... | 2279 | 474 | 0.207986 |
| 86 | 17.400000 | 47 | 173 | 01648583 | 47173 | Union | Union County | 06 | H1 | G4020 | 314 | 28940 | None | A | 578990181 | 61092965 | +36.2841401 | -083.8360878 | POLYGON ((-83.98571699999999 36.281478, -83.98... | 3517 | 611 | 0.173728 |
| 87 | 10.100000 | 47 | 175 | 01648584 | 47175 | Van buren | Van Buren County | 06 | H1 | G4020 | None | None | None | A | 708142475 | 2893424 | +35.6992446 | -085.4584114 | POLYGON ((-85.59742199999999 35.726036, -85.59... | 701 | 71 | 0.101284 |
| 88 | 14.200000 | 47 | 177 | 01639796 | 47177 | Warren | Warren County | 06 | H1 | G4020 | None | 32660 | None | A | 1120635730 | 3508343 | +35.6782817 | -085.7773633 | POLYGON ((-85.81362399999999 35.845816, -85.81... | 6469 | 920 | 0.142217 |
| 89 | 13.600000 | 47 | 179 | 01639797 | 47179 | Washington | Washington County | 06 | H1 | G4020 | 304 | 27740 | None | A | 845539916 | 8632655 | +36.2956649 | -082.4950374 | POLYGON ((-82.523303 36.434275, -82.5230299999... | 16232 | 2230 | 0.137383 |
| 90 | 17.300000 | 47 | 181 | 01639798 | 47181 | Wayne | Wayne County | 06 | H1 | G4020 | None | None | None | A | 1901310603 | 4023299 | +35.2426873 | -087.8197026 | POLYGON ((-87.981697 35.28794, -87.981695 35.2... | 2141 | 370 | 0.172816 |
| 91 | 11.900000 | 47 | 183 | 01639799 | 47183 | Weakley | Weakley County | 06 | H1 | G4020 | 542 | 32280 | None | A | 1503135455 | 3679548 | +36.3035229 | -088.7207846 | POLYGON ((-88.94070000000001 36.203893, -88.94... | 4136 | 493 | 0.119197 |
| 92 | 9.000000 | 47 | 185 | 01639800 | 47185 | White | White County | 06 | H1 | G4020 | None | None | None | A | 975578971 | 7128063 | +35.9270621 | -085.4557657 | (POLYGON ((-85.25227199999999 35.770612, -85.2... | 3864 | 349 | 0.090321 |
| 93 | 5.600000 | 47 | 187 | 01639801 | 47187 | Williamson | Williamson County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1508925443 | 3028823 | +35.8949720 | -086.8969580 | POLYGON ((-86.832753 36.041024, -86.832499 36.... | 41203 | 2600 | 0.063102 |
| 94 | 9.500000 | 47 | 189 | 01639802 | 47189 | Wilson | Wilson County | 06 | H1 | G4020 | 400 | 34980 | None | A | 1478433235 | 32037460 | +36.1484757 | -086.2902097 | POLYGON ((-86.442217 36.057074, -86.4435759999... | 21242 | 2355 | 0.110865 |
fig, ax = plt.subplots(1, figsize=(20, 12))
merged.plot(column='pct', cmap='Blues', linewidth=0.8, ax=ax, edgecolor='0.8')
ax.axis('off')
ax.set_title('Percentage of Chronically Absent Students in Tennessee', fontdict={'fontsize': '25', 'fontweight' : '3'})
# create an annotation for the data source
ax.annotate('Source: U.S. Census Bureau, 2010 & TN Dept. of Education 2017',xy=(0.1, .08), xycoords= 'figure fraction', horizontalalignment='left', verticalalignment='top', fontsize=12, color= '#555555')
# Create colorbar as a legend
sm = plt.cm.ScalarMappable(cmap='Blues', norm=plt.Normalize(vmin=0, vmax=1))
# empty array for the data range
sm._A = []
# add the colorbar to the figure
cbar = fig.colorbar(sm)
from bokeh.io import output_notebook, show, output_file
from bokeh.plotting import figure
from bokeh.models import GeoJSONDataSource, LinearColorMapper, ColorBar
from bokeh.palettes import brewer
from bokeh.io import curdoc, output_notebook
from bokeh.models import Slider, HoverTool
from bokeh.layouts import widgetbox, row, column
#Input GeoJSON source that contains features for plotting.
geosource = GeoJSONDataSource(geojson = json_data)
#Define a sequential multi-hue color palette.
palette = brewer['YlGnBu'][8]
#Reverse color order so that dark blue is highest percentage.???
palette = palette[::-1]
#Instantiate LinearColorMapper that linearly maps numbers in a range, into a sequence of colors.
color_mapper = LinearColorMapper(palette = palette, low = 0, high = 1)
#Define custom tick labels for color bar.
tick_labels = {'0': '0%', '5': '5%', '10':'10%', '15':'15%', '20':'20%', '25':'25%', '30':'30%','35':'35%', '40': '>40%'}
#Create color bar.
color_bar = ColorBar(color_mapper=color_mapper, label_standoff=8,width = 500, height = 20,
border_line_color=None,location = (0,0), orientation = 'horizontal', major_label_overrides = tick_labels)
#Create figure object.
#p = figure(title = 'Percentage of Students Chronically Absent, 2016-2017', plot_height = 400 , plot_width = 950, toolbar_location = None)
#p.xgrid.grid_line_color = None
#p.ygrid.grid_line_color = None
#Add hover tool
hover = HoverTool(tooltips = [ ('County','@NAMELSAD10'),('% chronically absent','@pct')])
#Create figure object.
p = figure(title = 'Percentage of Chronically Absent Students, 2016-2017', plot_height = 400 , plot_width = 800, toolbar_location = None, tools = [hover])
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
#Add patch renderer to figure.
p.patches('xs','ys', source = geosource,fill_color = {'field' :'pct', 'transform' : color_mapper},
line_color = 'black', line_width = 0.25, fill_alpha = 1)
#Specify figure layout.
p.add_layout(color_bar, 'below')
#Display figure inline in Jupyter Notebook.
output_notebook()
#Display figure.
show(p)
salary_tp=ddcmap.groupby('county')['classroom_teacher','principal'].median() #Median... attempted to avoid extreme outliers if present
salary_tp.head()
| classroom_teacher | principal | |
|---|---|---|
| county | ||
| Anderson | 46386.0 | 81234.0 |
| Bedford | 45733.0 | 78245.0 |
| Benton | 45908.0 | 64938.0 |
| Bledsoe | 48781.0 | 69205.0 |
| Blount | 61790.0 | 99120.0 |
tn_as=pd.merge(tn_abs2,salary_tp, left_on = 'NAME10', right_on='county') #tn_absence,salary... salary is based on median to avoid outliers
tn_as1=tn_as.iloc[:,[5, 19,20,21,22,23]]
health17tn = pd.read_csv('data/Outcomes and Factor Rankings Data 1719.csv')
health17tn.columns = ('FIPS', 'State', 'County', 'Health Outcomes Z-score', 'Health Outcomes Rank', 'Health Factors Z-score', 'Health Factors Rank', '')
health17tn
health17subranks = pd.read_csv('data/Outcomes and Factor Subrankings Data 1719.csv')
health17subranks.columns = ('FIPS', 'State', 'County', 'Length of Life Z-score', 'Length of Life Rank', ' Quality of Life Z-score', 'Quality of Life Rank', 'Health Behaviors Z-Score', 'Health Behaviors Rank', ' Clinical Care Z-score', 'Clinical Care Rank', 'Social & Economic Factors Z-score', 'Social & Economic Factors Rank', 'Physical Environment Z-score', 'Physical Environment Rank', '')
health17subranks.head()
disparaties17 = pd.read_csv('data/Ranked Measure Data 1719.csv')
more_disparaties17 = pd.read_csv('data/Additional Data Measures 1719.csv')
disparaties17['Unnamed: 2'] = disparaties17['Unnamed: 2'].str.capitalize()
disparaties17.head()
| Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Premature death | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Poor or fair health | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Poor physical health days | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Poor mental health days | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Low birthweight | Unnamed: 23 | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Adult smoking | Unnamed: 31 | Unnamed: 32 | Unnamed: 33 | Adult obesity | Unnamed: 35 | Unnamed: 36 | Unnamed: 37 | Food environment index | Unnamed: 39 | Physical inactivity | Unnamed: 41 | Unnamed: 42 | Unnamed: 43 | Access to exercise opportunities | Unnamed: 45 | Excessive drinking | Unnamed: 47 | Unnamed: 48 | Unnamed: 49 | Alcohol-impaired driving deaths | Unnamed: 51 | Unnamed: 52 | Unnamed: 53 | Unnamed: 54 | Unnamed: 55 | Sexually transmitted infections | Unnamed: 57 | Unnamed: 58 | Teen births | Unnamed: 60 | Unnamed: 61 | Unnamed: 62 | Unnamed: 63 | Unnamed: 64 | Unnamed: 65 | Uninsured | Unnamed: 67 | Unnamed: 68 | Unnamed: 69 | Unnamed: 70 | Primary care physicians | Unnamed: 72 | Unnamed: 73 | Unnamed: 74 | Dentists | Unnamed: 76 | Unnamed: 77 | Unnamed: 78 | Mental health providers | Unnamed: 80 | Unnamed: 81 | Unnamed: 82 | Preventable hospital stays | Unnamed: 84 | Unnamed: 85 | Unnamed: 86 | Unnamed: 87 | Mammography screening | Unnamed: 89 | Unnamed: 90 | Unnamed: 91 | Unnamed: 92 | Flu vaccinations | Unnamed: 94 | Unnamed: 95 | Unnamed: 96 | Unnamed: 97 | High school graduation | Unnamed: 99 | Unnamed: 100 | Some college | Unnamed: 102 | Unnamed: 103 | Unnamed: 104 | Unnamed: 105 | Unnamed: 106 | Unemployment | Unnamed: 108 | Unnamed: 109 | Unnamed: 110 | Children in poverty | Unnamed: 112 | Unnamed: 113 | Unnamed: 114 | Unnamed: 115 | Unnamed: 116 | Unnamed: 117 | Income inequality | Unnamed: 119 | Unnamed: 120 | Unnamed: 121 | Children in single-parent households | Unnamed: 123 | Unnamed: 124 | Unnamed: 125 | Unnamed: 126 | Unnamed: 127 | Social associations | Unnamed: 129 | Unnamed: 130 | Violent crime | Unnamed: 132 | Unnamed: 133 | Injury deaths | Unnamed: 135 | Unnamed: 136 | Unnamed: 137 | Unnamed: 138 | Air pollution - particulate matter | Unnamed: 140 | Drinking water violations | Unnamed: 142 | Severe housing problems | Unnamed: 144 | Unnamed: 145 | Unnamed: 146 | Unnamed: 147 | Unnamed: 148 | Unnamed: 149 | Driving alone to work | Unnamed: 151 | Unnamed: 152 | Unnamed: 153 | Unnamed: 154 | Unnamed: 155 | Unnamed: 156 | Long commute - driving alone | Unnamed: 158 | Unnamed: 159 | Unnamed: 160 | Unnamed: 161 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | FIPS | State | County | Years of Potential Life Lost Rate | 95% CI - Low | 95% CI - High | Z-Score | YPLL Rate (Black) | YPLL Rate (Hispanic) | YPLL Rate (White) | % Fair/Poor | 95% CI - Low | 95% CI - High | Z-Score | Physically Unhealthy Days | 95% CI - Low | 95% CI - High | Z-Score | Mentally Unhealthy Days | 95% CI - Low | 95% CI - High | Z-Score | Unreliable | % LBW | 95% CI - Low | 95% CI - High | Z-Score | % LBW (Black) | % LBW (Hispanic) | % LBW (White) | % Smokers | 95% CI - Low | 95% CI - High | Z-Score | % Obese | 95% CI - Low | 95% CI - High | Z-Score | Food Environment Index | Z-Score | % Physically Inactive | 95% CI - Low | 95% CI - High | Z-Score | % With Access | Z-Score | % Excessive Drinking | 95% CI - Low | 95% CI - High | Z-Score | # Alcohol-Impaired Driving Deaths | # Driving Deaths | % Alcohol-Impaired | 95% CI - Low | 95% CI - High | Z-Score | # Chlamydia Cases | Chlamydia Rate | Z-Score | Teen Birth Rate | 95% CI - Low | 95% CI - High | Z-Score | Teen Birth Rate (Black) | Teen Birth Rate (Hispanic) | Teen Birth Rate (White) | # Uninsured | % Uninsured | 95% CI - Low | 95% CI - High | Z-Score | # Primary Care Physicians | PCP Rate | PCP Ratio | Z-Score | # Dentists | Dentist Rate | Dentist Ratio | Z-Score | # Mental Health Providers | MHP Rate | MHP Ratio | Z-Score | Preventable Hosp. Rate | Z-Score | Preventable Hosp. Rate (Black) | Preventable Hosp. Rate (Hispanic) | Preventable Hosp. Rate (White) | % Screened | Z-Score | % Screened (Black) | % Screened (Hispanic) | % Screened (White) | % Vaccinated | Z-Score | % Vaccinated (Black) | % Vaccinated (Hispanic) | % Vaccinated (White) | Cohort Size | Graduation Rate | Z-Score | # Some College | Population | % Some College | 95% CI - Low | 95% CI - High | Z-Score | # Unemployed | Labor Force | % Unemployed | Z-Score | % Children in Poverty | 95% CI - Low | 95% CI - High | Z-Score | % Children in Poverty (Black) | % Children in Poverty (Hispanic) | % Children in Poverty (White) | 80th Percentile Income | 20th Percentile Income | Income Ratio | Z-Score | # Single-Parent Households | # Households | % Single-Parent Households | 95% CI - Low | 95% CI - High | Z-Score | # Associations | Association Rate | Z-Score | Annual Average Violent Crimes | Violent Crime Rate | Z-Score | # Injury Deaths | Injury Death Rate | 95% CI - Low | 95% CI - High | Z-Score | Average Daily PM2.5 | Z-Score | Presence of violation | Z-Score | % Severe Housing Problems | 95% CI - Low | 95% CI - High | Severe Housing Cost Burden | Overcrowding | Inadequate Facilities | Z-Score | % Drive Alone | 95% CI - Low | 95% CI - High | Z-Score | % Drive Alone (Black) | % Drive Alone (Hispanic) | % Drive Alone (White) | # Workers who Drive Alone | % Long Commute - Drives Alone | 95% CI - Low | 95% CI - High | Z-Score |
| 1 | 47000 | Tennessee | NaN | 9121 | 9039 | 9204 | NaN | NaN | NaN | NaN | 19 | 18 | 20 | NaN | 4.4 | 4.1 | 4.7 | NaN | 4.5 | 4.1 | 4.8 | NaN | NaN | 9 | 9 | 9 | NaN | NaN | NaN | NaN | 22 | 21 | 24 | NaN | 33 | NaN | NaN | NaN | 6.3 | NaN | 27 | NaN | NaN | NaN | 71 | NaN | 14 | 13 | 16 | NaN | 1311 | 4997 | 26 | 26 | 27 | NaN | 32304 | 489.4 | NaN | 33 | 33 | 34 | NaN | NaN | NaN | NaN | 581927 | 11 | 10 | 11 | NaN | 4802 | 72 | 1385:1 | NaN | 3574 | 53 | 1879:1 | NaN | 9531 | 142 | 705:1 | NaN | 5305 | NaN | NaN | NaN | NaN | 40 | NaN | NaN | NaN | NaN | 48 | NaN | NaN | NaN | NaN | 71587 | 90 | NaN | 1033412 | 1716447 | 60 | 60 | 61 | NaN | 118560 | 3198773 | 3.7 | NaN | 21 | 20 | 22 | NaN | NaN | NaN | NaN | 97093 | 20480 | 4.7 | NaN | 525915 | 1483144 | 35 | 35 | 36 | NaN | 7505 | 11.3 | NaN | 40973 | 621 | NaN | 28245 | 86 | 85 | 87 | NaN | 10.0 | NaN | NaN | NaN | 15 | 15 | 15 | NaN | NaN | NaN | NaN | 84 | 83 | 84 | NaN | NaN | NaN | NaN | 2466424 | 34 | 34 | 35 | NaN |
| 2 | 47001 | Tennessee | Anderson | 9536 | 8703 | 10368 | -0.40 | 11586 | NaN | 9749 | 19 | 18 | 20 | -0.51 | 4.7 | 4.5 | 4.9 | -0.47 | 4.7 | 4.5 | 4.9 | -0.35 | NaN | 9 | 8 | 10 | -0.10 | 12 | NaN | 9 | 21 | 20 | 22 | -0.68 | 32 | 26 | 38 | -0.56 | 7.5 | 0.23 | 28 | 23 | 34 | -0.41 | 66 | -0.62 | 14 | 13 | 14 | 0.00 | 18 | 60 | 30 | 23 | 37 | 0.14 | 263 | 347.2 | -0.09 | 37 | 34 | 40 | -0.19 | 29 | 24 | 38 | 5550 | 9 | 8 | 11 | -1.31 | 46 | 61 | 1651:1 | -0.49 | 55 | 72 | 1386:1 | -2.03 | 69 | 90 | 1105:1 | -0.26 | 4867 | -0.58 | 5397 | NaN | 4825 | 49 | -1.98 | 53 | 54 | 49 | 54 | -1.49 | 42 | 43 | 55 | 859 | 92 | 0.15 | 10273 | 17614 | 58 | 54 | 63 | -0.98 | 1333 | 34175 | 3.9 | -0.51 | 22 | 16 | 28 | -0.35 | 26 | 34 | 25 | 96851 | 19940 | 4.9 | 0.62 | 5894 | 15656 | 38 | 32 | 43 | 0.65 | 118 | 15.5 | -1.22 | 251 | 401 | 0.05 | 404 | 107 | 96 | 117 | 0.46 | 10.3 | 0.55 | No | -0.59 | 13 | 12 | 15 | 12 | 1 | 1 | -0.08 | 87 | 85 | 89 | 0.77 | 95 | 77 | 90 | 27323 | 34 | 31 | 37 | -0.42 |
| 3 | 47003 | Tennessee | Bedford | 9762 | 8769 | 10754 | -0.28 | 9265 | 4454 | 10683 | 22 | 21 | 22 | 0.45 | 4.8 | 4.6 | 5.0 | -0.10 | 4.7 | 4.5 | 4.9 | -0.20 | NaN | 9 | 8 | 10 | -0.11 | 14 | 6 | 9 | 21 | 21 | 22 | -0.36 | 33 | 26 | 39 | -0.30 | 7.9 | -0.38 | 33 | 26 | 39 | 0.79 | 51 | 0.13 | 15 | 14 | 15 | 0.68 | 24 | 47 | 51 | 45 | 57 | 2.08 | 153 | 324.3 | -0.20 | 43 | 39 | 47 | 0.42 | 33 | 49 | 43 | 5173 | 13 | 11 | 15 | 1.19 | 18 | 38 | 2638:1 | 0.27 | 12 | 25 | 4010:1 | 0.57 | 33 | 69 | 1458:1 | 0.04 | 6034 | 0.09 | 3236 | NaN | 6300 | 42 | -0.65 | 51 | 29 | 41 | 45 | 0.10 | 36 | 21 | 45 | 571 | 91 | 0.45 | 5013 | 12114 | 41 | 36 | 46 | 0.64 | 804 | 20539 | 3.9 | -0.49 | 23 | 17 | 29 | -0.19 | 29 | 29 | 19 | 82588 | 21083 | 3.9 | -1.24 | 4316 | 11929 | 36 | 30 | 42 | 0.44 | 45 | 9.5 | 0.36 | 200 | 425 | 0.17 | 203 | 86 | 74 | 98 | -0.50 | 10.5 | 0.95 | Yes | 1.66 | 15 | 13 | 18 | 12 | 4 | 1 | 0.72 | 82 | 79 | 85 | -0.74 | 81 | 64 | 81 | 17179 | 36 | 31 | 40 | -0.25 |
| 4 | 47005 | Tennessee | Benton | 12828 | 10692 | 14965 | 1.40 | NaN | NaN | NaN | 21 | 20 | 22 | 0.32 | 5.2 | 5.0 | 5.5 | 1.07 | 5.1 | 4.9 | 5.4 | 1.34 | NaN | 8 | 7 | 10 | -0.63 | NaN | NaN | NaN | 23 | 22 | 24 | 0.24 | 35 | 28 | 41 | 0.54 | 7.4 | 0.38 | 32 | 25 | 39 | 0.52 | 48 | 0.27 | 12 | 12 | 13 | -1.23 | 11 | 27 | 41 | 31 | 50 | 1.13 | 56 | 347.2 | -0.09 | 50 | 42 | 58 | 1.15 | NaN | NaN | NaN | 1431 | 12 | 10 | 13 | 0.41 | 3 | 19 | 5338:1 | 0.91 | 3 | 19 | 5329:1 | 0.91 | 6 | 38 | 2664:1 | 0.48 | 6528 | 0.37 | NaN | NaN | NaN | 32 | 1.25 | NaN | NaN | NaN | 47 | -0.25 | 37 | 40 | 48 | 166 | 96 | -0.77 | 1515 | 3422 | 44 | 36 | 52 | 0.36 | 364 | 6769 | 5.4 | 1.28 | 30 | 21 | 39 | 0.91 | NaN | 93 | 28 | 69035 | 14105 | 4.9 | 0.69 | 1152 | 3209 | 36 | 25 | 47 | 0.40 | 21 | 13.1 | -0.59 | 25 | 152 | -1.15 | 130 | 161 | 134 | 189 | 3.00 | 10.0 | -0.06 | No | -0.59 | 16 | 13 | 19 | 13 | 3 | 1 | 1.07 | 87 | 83 | 91 | 0.83 | NaN | NaN | NaN | 4807 | 27 | 22 | 32 | -1.04 |
disparaties179 = disparaties17
disparaties179.columns = disparaties17.iloc[0,:]
disparaties179.head()
more_disparaties17['Unnamed: 2'] = more_disparaties17['Unnamed: 2'].str.capitalize()
health17tn['County'] = health17tn['County'].str.capitalize()
health17subranks['County'] = health17subranks['County'].str.capitalize()
abs_health=pd.merge(tn_as1,health17tn, left_on = 'NAME10', right_on='County')
abs_health=abs_health.iloc[:,[0,1,2,3,4,5,9,10,11,12,13]]
abs_health.columns
Index(['NAME10', 'n_students', 'n_chronically_absent', 'pct', 'classroom_teacher', 'principal', 'Health Outcomes Z-score', 'Health Outcomes Rank', 'Health Factors Z-score', 'Health Factors Rank', ''], dtype='object')
abs_health['Health Factors Rank']=pd.to_numeric(abs_health.iloc[:,-2])
abs_health['Health Factors Z-score']=pd.to_numeric(abs_health.iloc[:,-3])
abs_health['Health Outcomes Z-score']=pd.to_numeric(abs_health.iloc[:,6])
abs_health['Health Outcomes Rank']=pd.to_numeric(abs_health.iloc[:,7])
corr = abs_health.corr()
# plot the heatmap
sns.heatmap(corr)
<matplotlib.axes._subplots.AxesSubplot at 0x27368bea748>
abs_health2=pd.merge(tn_as1,health17subranks, left_on = 'NAME10', right_on='County')
abs_health2 = abs_health2.iloc[:,[0,1,2,3,4,5,9,10,11,12,13,14,15,16,17,18,19,20]]
abs_health2.head()
| NAME10 | n_students | n_chronically_absent | pct | classroom_teacher | principal | Length of Life Z-score | Length of Life Rank | Quality of Life Z-score | Quality of Life Rank | Health Behaviors Z-Score | Health Behaviors Rank | Clinical Care Z-score | Clinical Care Rank | Social & Economic Factors Z-score | Social & Economic Factors Rank | Physical Environment Z-score | Physical Environment Rank | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Anderson | 11621 | 1432 | 0.123225 | 46386.0 | 81234.0 | -0.20 | 30 | -0.15 | 30 | -0.11 | 19 | -0.22 | 7 | -0.10 | 31 | 0.01 | 57 |
| 1 | Bedford | 8502 | 1088 | 0.127970 | 45733.0 | 78245.0 | -0.14 | 34 | -0.01 | 46 | 0.03 | 56 | 0.06 | 67 | -0.03 | 42 | 0.06 | 86 |
| 2 | Benton | 2123 | 192 | 0.090438 | 45908.0 | 64938.0 | 0.70 | 86 | 0.15 | 65 | 0.10 | 74 | 0.11 | 81 | 0.23 | 81 | 0.01 | 59 |
| 3 | Bledsoe | 1681 | 279 | 0.165973 | 48781.0 | 69205.0 | -0.69 | 7 | -0.15 | 32 | 0.33 | 93 | 0.19 | 90 | 0.41 | 93 | -0.05 | 11 |
| 4 | Blount | 17779 | 1338 | 0.075257 | 61790.0 | 99120.0 | -0.55 | 14 | -0.50 | 9 | -0.16 | 10 | -0.18 | 9 | -0.32 | 7 | 0.04 | 80 |
abs_health2a=abs_health2.iloc[:,1:].astype(float)
abs_health2a['County']=abs_health['NAME10']
abs_health2a.head()
| n_students | n_chronically_absent | pct | classroom_teacher | principal | Length of Life Z-score | Length of Life Rank | Quality of Life Z-score | Quality of Life Rank | Health Behaviors Z-Score | Health Behaviors Rank | Clinical Care Z-score | Clinical Care Rank | Social & Economic Factors Z-score | Social & Economic Factors Rank | Physical Environment Z-score | Physical Environment Rank | County | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 11621.0 | 1432.0 | 0.123225 | 46386.0 | 81234.0 | -0.20 | 30.0 | -0.15 | 30.0 | -0.11 | 19.0 | -0.22 | 7.0 | -0.10 | 31.0 | 0.01 | 57.0 | Anderson |
| 1 | 8502.0 | 1088.0 | 0.127970 | 45733.0 | 78245.0 | -0.14 | 34.0 | -0.01 | 46.0 | 0.03 | 56.0 | 0.06 | 67.0 | -0.03 | 42.0 | 0.06 | 86.0 | Bedford |
| 2 | 2123.0 | 192.0 | 0.090438 | 45908.0 | 64938.0 | 0.70 | 86.0 | 0.15 | 65.0 | 0.10 | 74.0 | 0.11 | 81.0 | 0.23 | 81.0 | 0.01 | 59.0 | Benton |
| 3 | 1681.0 | 279.0 | 0.165973 | 48781.0 | 69205.0 | -0.69 | 7.0 | -0.15 | 32.0 | 0.33 | 93.0 | 0.19 | 90.0 | 0.41 | 93.0 | -0.05 | 11.0 | Bledsoe |
| 4 | 17779.0 | 1338.0 | 0.075257 | 61790.0 | 99120.0 | -0.55 | 14.0 | -0.50 | 9.0 | -0.16 | 10.0 | -0.18 | 9.0 | -0.32 | 7.0 | 0.04 | 80.0 | Blount |
corr = abs_health2a.corr()
# plot the heatmap
sns.heatmap(corr)
<matplotlib.axes._subplots.AxesSubplot at 0x2736d53a550>
abs_health3=pd.merge(tn_as,disparaties17, left_on = 'NAME10', right_on='Unnamed: 2')
abs_health3.head()
| pct_chronically_absent | STATEFP10 | COUNTYFP10 | COUNTYNS10 | GEOID10 | NAME10 | NAMELSAD10 | LSAD10 | CLASSFP10 | MTFCC10 | CSAFP10 | CBSAFP10 | METDIVFP10 | FUNCSTAT10 | ALAND10 | AWATER10 | INTPTLAT10 | INTPTLON10 | geometry | n_students | n_chronically_absent | pct | classroom_teacher | principal | Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Premature death | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Poor or fair health | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Poor physical health days | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Poor mental health days | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Low birthweight | Unnamed: 23 | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Adult smoking | Unnamed: 31 | Unnamed: 32 | Unnamed: 33 | Adult obesity | Unnamed: 35 | Unnamed: 36 | Unnamed: 37 | Food environment index | Unnamed: 39 | Physical inactivity | Unnamed: 41 | Unnamed: 42 | Unnamed: 43 | Access to exercise opportunities | Unnamed: 45 | Excessive drinking | Unnamed: 47 | Unnamed: 48 | Unnamed: 49 | Alcohol-impaired driving deaths | Unnamed: 51 | Unnamed: 52 | Unnamed: 53 | Unnamed: 54 | Unnamed: 55 | Sexually transmitted infections | Unnamed: 57 | Unnamed: 58 | Teen births | Unnamed: 60 | Unnamed: 61 | Unnamed: 62 | Unnamed: 63 | Unnamed: 64 | Unnamed: 65 | Uninsured | Unnamed: 67 | Unnamed: 68 | Unnamed: 69 | Unnamed: 70 | Primary care physicians | Unnamed: 72 | Unnamed: 73 | Unnamed: 74 | Dentists | Unnamed: 76 | Unnamed: 77 | Unnamed: 78 | Mental health providers | Unnamed: 80 | Unnamed: 81 | Unnamed: 82 | Preventable hospital stays | Unnamed: 84 | Unnamed: 85 | Unnamed: 86 | Unnamed: 87 | Mammography screening | Unnamed: 89 | Unnamed: 90 | Unnamed: 91 | Unnamed: 92 | Flu vaccinations | Unnamed: 94 | Unnamed: 95 | Unnamed: 96 | Unnamed: 97 | High school graduation | Unnamed: 99 | Unnamed: 100 | Some college | Unnamed: 102 | Unnamed: 103 | Unnamed: 104 | Unnamed: 105 | Unnamed: 106 | Unemployment | Unnamed: 108 | Unnamed: 109 | Unnamed: 110 | Children in poverty | Unnamed: 112 | Unnamed: 113 | Unnamed: 114 | Unnamed: 115 | Unnamed: 116 | Unnamed: 117 | Income inequality | Unnamed: 119 | Unnamed: 120 | Unnamed: 121 | Children in single-parent households | Unnamed: 123 | Unnamed: 124 | Unnamed: 125 | Unnamed: 126 | Unnamed: 127 | Social associations | Unnamed: 129 | Unnamed: 130 | Violent crime | Unnamed: 132 | Unnamed: 133 | Injury deaths | Unnamed: 135 | Unnamed: 136 | Unnamed: 137 | Unnamed: 138 | Air pollution - particulate matter | Unnamed: 140 | Drinking water violations | Unnamed: 142 | Severe housing problems | Unnamed: 144 | Unnamed: 145 | Unnamed: 146 | Unnamed: 147 | Unnamed: 148 | Unnamed: 149 | Driving alone to work | Unnamed: 151 | Unnamed: 152 | Unnamed: 153 | Unnamed: 154 | Unnamed: 155 | Unnamed: 156 | Long commute - driving alone | Unnamed: 158 | Unnamed: 159 | Unnamed: 160 | Unnamed: 161 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 11.066667 | 47 | 001 | 01639722 | 47001 | Anderson | Anderson County | 06 | H1 | G4020 | 314 | 28940 | None | A | 873245292 | 19771988 | +36.1167307 | -084.1954177 | POLYGON ((-84.33464599999999 36.0302, -84.3346... | 11621 | 1432 | 0.123225 | 46386.0 | 81234.0 | 47001 | Tennessee | Anderson | 9536 | 8703 | 10368 | -0.40 | 11586 | NaN | 9749 | 19 | 18 | 20 | -0.51 | 4.7 | 4.5 | 4.9 | -0.47 | 4.7 | 4.5 | 4.9 | -0.35 | NaN | 9 | 8 | 10 | -0.10 | 12 | NaN | 9 | 21 | 20 | 22 | -0.68 | 32 | 26 | 38 | -0.56 | 7.5 | 0.23 | 28 | 23 | 34 | -0.41 | 66 | -0.62 | 14 | 13 | 14 | 0.00 | 18 | 60 | 30 | 23 | 37 | 0.14 | 263 | 347.2 | -0.09 | 37 | 34 | 40 | -0.19 | 29 | 24 | 38 | 5550 | 9 | 8 | 11 | -1.31 | 46 | 61 | 1651:1 | -0.49 | 55 | 72 | 1386:1 | -2.03 | 69 | 90 | 1105:1 | -0.26 | 4867 | -0.58 | 5397 | NaN | 4825 | 49 | -1.98 | 53 | 54 | 49 | 54 | -1.49 | 42 | 43 | 55 | 859 | 92 | 0.15 | 10273 | 17614 | 58 | 54 | 63 | -0.98 | 1333 | 34175 | 3.9 | -0.51 | 22 | 16 | 28 | -0.35 | 26 | 34 | 25 | 96851 | 19940 | 4.9 | 0.62 | 5894 | 15656 | 38 | 32 | 43 | 0.65 | 118 | 15.5 | -1.22 | 251 | 401 | 0.05 | 404 | 107 | 96 | 117 | 0.46 | 10.3 | 0.55 | No | -0.59 | 13 | 12 | 15 | 12 | 1 | 1 | -0.08 | 87 | 85 | 89 | 0.77 | 95 | 77 | 90 | 27323 | 34 | 31 | 37 | -0.42 |
| 1 | 12.800000 | 47 | 003 | 01639723 | 47003 | Bedford | Bedford County | 06 | H1 | G4020 | None | 43180 | None | A | 1226710123 | 2983154 | +35.5136604 | -086.4582939 | POLYGON ((-86.499674 35.359984, -86.499798 35.... | 8502 | 1088 | 0.127970 | 45733.0 | 78245.0 | 47003 | Tennessee | Bedford | 9762 | 8769 | 10754 | -0.28 | 9265 | 4454 | 10683 | 22 | 21 | 22 | 0.45 | 4.8 | 4.6 | 5.0 | -0.10 | 4.7 | 4.5 | 4.9 | -0.20 | NaN | 9 | 8 | 10 | -0.11 | 14 | 6 | 9 | 21 | 21 | 22 | -0.36 | 33 | 26 | 39 | -0.30 | 7.9 | -0.38 | 33 | 26 | 39 | 0.79 | 51 | 0.13 | 15 | 14 | 15 | 0.68 | 24 | 47 | 51 | 45 | 57 | 2.08 | 153 | 324.3 | -0.20 | 43 | 39 | 47 | 0.42 | 33 | 49 | 43 | 5173 | 13 | 11 | 15 | 1.19 | 18 | 38 | 2638:1 | 0.27 | 12 | 25 | 4010:1 | 0.57 | 33 | 69 | 1458:1 | 0.04 | 6034 | 0.09 | 3236 | NaN | 6300 | 42 | -0.65 | 51 | 29 | 41 | 45 | 0.10 | 36 | 21 | 45 | 571 | 91 | 0.45 | 5013 | 12114 | 41 | 36 | 46 | 0.64 | 804 | 20539 | 3.9 | -0.49 | 23 | 17 | 29 | -0.19 | 29 | 29 | 19 | 82588 | 21083 | 3.9 | -1.24 | 4316 | 11929 | 36 | 30 | 42 | 0.44 | 45 | 9.5 | 0.36 | 200 | 425 | 0.17 | 203 | 86 | 74 | 98 | -0.50 | 10.5 | 0.95 | Yes | 1.66 | 15 | 13 | 18 | 12 | 4 | 1 | 0.72 | 82 | 79 | 85 | -0.74 | 81 | 64 | 81 | 17179 | 36 | 31 | 40 | -0.25 |
| 2 | 9.000000 | 47 | 005 | 01639724 | 47005 | Benton | Benton County | 06 | H1 | G4020 | None | None | None | A | 1020822586 | 109009079 | +36.0692530 | -088.0712118 | POLYGON ((-87.95178799999999 36.225321, -87.95... | 2123 | 192 | 0.090438 | 45908.0 | 64938.0 | 47005 | Tennessee | Benton | 12828 | 10692 | 14965 | 1.40 | NaN | NaN | NaN | 21 | 20 | 22 | 0.32 | 5.2 | 5.0 | 5.5 | 1.07 | 5.1 | 4.9 | 5.4 | 1.34 | NaN | 8 | 7 | 10 | -0.63 | NaN | NaN | NaN | 23 | 22 | 24 | 0.24 | 35 | 28 | 41 | 0.54 | 7.4 | 0.38 | 32 | 25 | 39 | 0.52 | 48 | 0.27 | 12 | 12 | 13 | -1.23 | 11 | 27 | 41 | 31 | 50 | 1.13 | 56 | 347.2 | -0.09 | 50 | 42 | 58 | 1.15 | NaN | NaN | NaN | 1431 | 12 | 10 | 13 | 0.41 | 3 | 19 | 5338:1 | 0.91 | 3 | 19 | 5329:1 | 0.91 | 6 | 38 | 2664:1 | 0.48 | 6528 | 0.37 | NaN | NaN | NaN | 32 | 1.25 | NaN | NaN | NaN | 47 | -0.25 | 37 | 40 | 48 | 166 | 96 | -0.77 | 1515 | 3422 | 44 | 36 | 52 | 0.36 | 364 | 6769 | 5.4 | 1.28 | 30 | 21 | 39 | 0.91 | NaN | 93 | 28 | 69035 | 14105 | 4.9 | 0.69 | 1152 | 3209 | 36 | 25 | 47 | 0.40 | 21 | 13.1 | -0.59 | 25 | 152 | -1.15 | 130 | 161 | 134 | 189 | 3.00 | 10.0 | -0.06 | No | -0.59 | 16 | 13 | 19 | 13 | 3 | 1 | 1.07 | 87 | 83 | 91 | 0.83 | NaN | NaN | NaN | 4807 | 27 | 22 | 32 | -1.04 |
| 3 | 16.600000 | 47 | 007 | 01639725 | 47007 | Bledsoe | Bledsoe County | 06 | H1 | G4020 | None | None | None | A | 1052635810 | 838365 | +35.5936682 | -085.2059790 | POLYGON ((-85.277034 35.390432, -85.277891 35.... | 1681 | 279 | 0.165973 | 48781.0 | 69205.0 | 47007 | Tennessee | Bledsoe | 7735 | 6103 | 9367 | -1.39 | NaN | NaN | NaN | 22 | 21 | 23 | 0.64 | 5.1 | 4.9 | 5.4 | 0.81 | 4.8 | 4.5 | 5.0 | 0.05 | NaN | 7 | 5 | 9 | -1.51 | NaN | NaN | NaN | 26 | 25 | 27 | 1.64 | 35 | 28 | 42 | 0.63 | 7.8 | -0.23 | 29 | 23 | 36 | -0.30 | 25 | 1.41 | 14 | 13 | 15 | 0.13 | 4 | 8 | 50 | 32 | 65 | 1.98 | 180 | 1241.2 | 3.00 | 42 | 34 | 51 | 0.31 | NaN | NaN | NaN | 1331 | 14 | 12 | 16 | 1.88 | 1 | 7 | 14675:1 | 1.31 | 3 | 20 | 4906:1 | 0.82 | 4 | 27 | 3679:1 | 0.62 | 5025 | -0.49 | NaN | NaN | NaN | 36 | 0.49 | NaN | NaN | NaN | 34 | 2.04 | NaN | NaN | NaN | 124 | 85 | 1.79 | 1329 | 3954 | 34 | 27 | 40 | 1.38 | 253 | 4317 | 5.9 | 1.87 | 30 | 21 | 40 | 0.97 | 20 | 84 | 25 | 81994 | 17665 | 4.6 | 0.19 | 679 | 2313 | 29 | 21 | 38 | -0.55 | 7 | 4.8 | 1.58 | 24 | 173 | -1.05 | 60 | 85 | 65 | 109 | -0.56 | 9.4 | -1.26 | No | -0.59 | 18 | 13 | 22 | 13 | 3 | 2 | 1.73 | 77 | 71 | 83 | -2.32 | NaN | NaN | NaN | 3942 | 51 | 40 | 61 | 1.17 |
| 4 | 7.100000 | 47 | 009 | 01639726 | 47009 | Blount | Blount County | 06 | H1 | G4020 | 314 | 28940 | None | A | 1447041818 | 20307831 | +35.6881849 | -083.9229731 | POLYGON ((-84.14251999999999 35.796954, -84.14... | 17779 | 1338 | 0.075257 | 61790.0 | 99120.0 | 47009 | Tennessee | Blount | 8268 | 7676 | 8860 | -1.09 | 8794 | NaN | 8458 | 17 | 16 | 17 | -1.44 | 4.6 | 4.4 | 4.8 | -0.78 | 4.5 | 4.3 | 4.7 | -0.96 | NaN | 8 | 7 | 8 | -0.92 | 11 | 4 | 8 | 19 | 18 | 20 | -1.47 | 35 | 29 | 41 | 0.54 | 7.7 | -0.08 | 26 | 21 | 31 | -1.15 | 67 | -0.66 | 14 | 13 | 15 | 0.32 | 34 | 109 | 31 | 26 | 36 | 0.25 | 473 | 371.7 | 0.04 | 30 | 28 | 32 | -0.83 | 32 | 39 | 30 | 10388 | 10 | 9 | 11 | -0.69 | 92 | 72 | 1399:1 | -0.85 | 75 | 58 | 1732:1 | -1.24 | 154 | 119 | 844:1 | -0.65 | 4892 | -0.57 | 5676 | 8481 | 4884 | 45 | -1.22 | 61 | 30 | 45 | 54 | -1.49 | 43 | 37 | 54 | 1330 | 94 | -0.44 | 17521 | 29975 | 58 | 55 | 62 | -0.99 | 2152 | 61819 | 3.5 | -1.02 | 17 | 13 | 21 | -1.13 | 28 | 39 | 17 | 96133 | 22746 | 4.2 | -0.63 | 6977 | 26229 | 27 | 23 | 30 | -0.95 | 146 | 11.3 | -0.13 | 449 | 354 | -0.18 | 517 | 81 | 74 | 88 | -0.74 | 10.1 | 0.15 | Yes | 1.66 | 13 | 11 | 14 | 12 | 1 | 1 | -0.40 | 86 | 84 | 87 | 0.41 | 90 | 74 | 87 | 49316 | 36 | 33 | 38 | -0.23 |
abs_health_3=abs_health3.iloc[:,[5,21,22,23,38,42,47,54,58,62,64,83,91,95,99,103,117,133,135,148,155,167]]
abs_health_3.columns = ('NAME10', 'pct', 'classroom_teacher', 'principal', 'Poor physical health days', 'Poor mental health days', '% Low Birth Weight', 'Adult smoking', 'Adult obesity', 'Food environment index', 'Physical inactivity', 'Teen births', '% Uninsured', 'Primary care physicians', 'Dentists', 'Mental health providers', 'Flu vaccinations', '% Unemployed', 'Children in poverty', '% Single-Parent Household', 'Violent crime', 'Severe housing problems')
abs_health_3a = abs_health_3.iloc[:,1:].astype(float)
abs_health_3a['County'] = abs_health3['NAME10']
corr = abs_health_3a.corr()
# plot the heatmap
sns.heatmap(corr)
<matplotlib.axes._subplots.AxesSubplot at 0x2736d638630>
demographics = more_disparaties17.iloc[:,89:]
demographics['County'] = more_disparaties17['Unnamed: 2']
C:\Users\unews\Anaconda3\lib\site-packages\ipykernel_launcher.py:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy """Entry point for launching an IPython kernel.
demographics.columns=demographics.iloc[0,:]
demographics = demographics.iloc[1,:]
abs_health4=pd.merge(tn_as,more_disparaties17, left_on = 'NAME10', right_on='Unnamed: 2')
more=more_disparaties17.iloc[:,[2,3,9,16,17,23,24,30,33,36,39,40,41,42,43,44,45,46,51,54,55,58,59,65,71,74,77,81,82,85,86]]
more.columns = ('County', 'Life expectancy', 'Premature age-adjusted mortality', 'Child mortality # Deaths', 'Child Mortality Rate', 'Infant mortality # of Deaths', 'Infant Mortality Rate', '% Frequent physical distress', '%Frequent mental distress', '% Diabetes prevalence', 'HIV prevalence # of cases', 'HIV Prevalence Rate', '# of Food insecure', '% of Food Insecure', '# with Limited access to healthy foods', '% of limited access to healthy foods', '# of Drug overdose deaths', 'Drug Overdose Mortality Rate', '% Insufficient sleep', '# of Uninsured adults', '% of Uninsured Adults', '# of Uninsured children', '% of Uninsured children', 'Median household income', '%Children eligible for free or reduced price lunch', 'Homicides', '# of Firearm fatalities', '# of Homeowners', '% of Homeowners', '# of Households with Severe housing cost burden', '% of Severe Housing Cost Burden')
more_disp=pd.merge(tn_as1,more, left_on = 'NAME10', right_on = 'County')##USE
type(more_disp.iloc[1,18])
str
more_disp.columns
Index(['NAME10', 'n_students', 'n_chronically_absent', 'pct', 'classroom_teacher', 'principal', 'Life expectancy', 'Premature age-adjusted mortality', 'Child mortality # Deaths', 'Child Mortality Rate', 'Infant mortality # of Deaths', 'Infant Mortality Rate', '% Frequent physical distress', '%Frequent mental distress', '% Diabetes prevalence', 'HIV prevalence # of cases', 'HIV Prevalence Rate', '# of Food insecure', '% of Food Insecure', '# with Limited access to healthy foods', '% of limited access to healthy foods', '# of Drug overdose deaths', 'Drug Overdose Mortality Rate', '% Insufficient sleep', '# of Uninsured adults', '% of Uninsured Adults', '# of Uninsured children', '% of Uninsured children', 'Median household income', '%Children eligible for free or reduced price lunch', 'Homicides', '# of Firearm fatalities', '# of Homeowners', '% of Homeowners', '# of Households with Severe housing cost burden', '% of Severe Housing Cost Burden'], dtype='object')
more_disparaties17
| Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Life expectancy | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Premature age-adjusted mortality | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Unnamed: 14 | Unnamed: 15 | Child mortality | Unnamed: 17 | Unnamed: 18 | Unnamed: 19 | Unnamed: 20 | Unnamed: 21 | Unnamed: 22 | Infant mortality | Unnamed: 24 | Unnamed: 25 | Unnamed: 26 | Unnamed: 27 | Unnamed: 28 | Unnamed: 29 | Frequent physical distress | Unnamed: 31 | Unnamed: 32 | Frequent mental distress | Unnamed: 34 | Unnamed: 35 | Diabetes prevalence | Unnamed: 37 | Unnamed: 38 | HIV prevalence | Unnamed: 40 | Food insecurity | Unnamed: 42 | Limited access to healthy foods | Unnamed: 44 | Drug overdose deaths | Unnamed: 46 | Motor vehicle crash deaths | Unnamed: 48 | Unnamed: 49 | Unnamed: 50 | Insufficient sleep | Unnamed: 52 | Unnamed: 53 | Uninsured adults | Unnamed: 55 | Unnamed: 56 | Unnamed: 57 | Uninsured children | Unnamed: 59 | Unnamed: 60 | Unnamed: 61 | Other primary care providers | Unnamed: 63 | Disconnected youth | Median household income | Unnamed: 66 | Unnamed: 67 | Unnamed: 68 | Unnamed: 69 | Unnamed: 70 | Children eligible for free or reduced price lunch | Residential segregation - black/white | Residential segregation - non-white/white | Homicides | Unnamed: 75 | Unnamed: 76 | Firearm fatalities | Unnamed: 78 | Unnamed: 79 | Unnamed: 80 | Homeownership | Unnamed: 82 | Unnamed: 83 | Unnamed: 84 | Severe housing cost burden | Unnamed: 86 | Unnamed: 87 | Unnamed: 88 | Demographics | Unnamed: 90 | Unnamed: 91 | Unnamed: 92 | Unnamed: 93 | Unnamed: 94 | Unnamed: 95 | Unnamed: 96 | Unnamed: 97 | Unnamed: 98 | Unnamed: 99 | Unnamed: 100 | Unnamed: 101 | Unnamed: 102 | Unnamed: 103 | Unnamed: 104 | Unnamed: 105 | Unnamed: 106 | Unnamed: 107 | Unnamed: 108 | Unnamed: 109 | Unnamed: 110 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | FIPS | State | County | Life Expectancy | 95% CI - Low | 95% CI - High | Life Expectancy (Black) | Life Expectancy (Hispanic) | Life Expectancy (White) | # Deaths | Age-Adjusted Mortality | 95% CI - Low | 95% CI - High | Age-Adjusted Mortality (Black) | Age-Adjusted Mortality (Hispanic) | Age-Adjusted Mortality (White) | # Deaths | Child Mortality Rate | 95% CI - Low | 95% CI - High | Child Mortality Rate (Black) | Child Mortality Rate (Hispanic) | Child Mortality Rate (White) | # Deaths | Infant Mortality Rate | 95% CI - Low | 95% CI - High | Infant Mortality Rate (Black) | Infant Mortality Rate (Hispanic) | Infant Mortality Rate (White) | % Frequent Physical Distress | 95% CI - Low | 95% CI - High | % Frequent Mental Distress | 95% CI - Low | 95% CI - High | % Diabetic | 95% CI - Low | 95% CI - High | # HIV Cases | HIV Prevalence Rate | # Food Insecure | % Food Insecure | # Limited Access | % Limited Access | # Drug Overdose Deaths | Drug Overdose Mortality Rate | # Motor Vehicle Deaths | MV Mortality Rate | 95% CI - Low | 95% CI - High | % Insufficient Sleep | 95% CI - Low | 95% CI - High | # Uninsured | % Uninsured | 95% CI - Low | 95% CI - High | # Uninsured | % Uninsured | 95% CI - Low | 95% CI - High | Other PCP Rate | Other PCP Ratio | % Disconnected Youth | Household Income | 95% CI - Low | 95% CI - High | Household income (Black) | Household income (Hispanic) | Household income (White) | % Free or Reduced Lunch | Segregation index | Segregation Index | Homicide Rate | 95% CI - Low | 95% CI - High | # Firearm Fatalities | Firearm Fatalities Rate | 95% CI - Low | 95% CI - High | # Homeowners | % Homeowners | 95% CI - Low | 95% CI - High | # Households with Severe Cost Burden | % Severe Housing Cost Burden | 95% CI - Low | 95% CI - High | Population | % < 18 | % 65 and over | # African American | % African American | # American Indian/Alaskan Native | % American Indian/Alaskan Native | # Asian | % Asian | # Native Hawaiian/Other Pacific Islander | % Native Hawaiian/Other Pacific Islander | # Hispanic | % Hispanic | # Non-Hispanic White | % Non-Hispanic White | # Not Proficient in English | % Not Proficient in English | 95% CI - Low | 95% CI - High | % Female | # Rural | % Rural |
| 1 | 47000 | Tennessee | NaN | 76.1 | 76.0 | 76.2 | NaN | NaN | NaN | 104195 | 447 | 444 | 449 | NaN | NaN | NaN | 3725 | 62 | 60 | 64 | NaN | NaN | NaN | 4045 | 7 | 7 | 7 | NaN | NaN | NaN | 14 | 13 | 15 | 14 | 13 | 15 | 13 | NaN | NaN | 16425 | 297 | 967430 | 15 | 536900 | 8 | 4863 | 24 | 6936 | 15 | 15 | 16 | 36 | 35 | 38 | 530070 | 13 | 13 | 14 | 56887 | 4 | 3 | 4 | 127 | 787:1 | 8 | 51319 | 50836 | 51802 | NaN | NaN | NaN | NaN | 67 | 58 | 7 | 7 | 7 | 5513 | 17 | 16 | 17 | 1688565 | 66 | 66 | 67 | 311113 | 13 | 13 | 13 | 6715984 | 22.4 | 16.0 | 1126692 | 16.8 | 30876 | 0.5 | 125244 | 1.9 | 6428 | 0.1 | 366554 | 5.5 | 4963780 | 73.9 | 94475 | 2 | 1 | 2 | 51.2 | 2132860 | 33.6 |
| 2 | 47001 | Tennessee | Anderson | 76.1 | 75.4 | 76.8 | 74.8 | 92.3 | 75.9 | 1299 | 451 | 426 | 477 | 536 | NaN | 460 | 43 | 67 | 49 | 91 | NaN | NaN | NaN | 45 | 8 | 6 | 11 | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 12 | 9 | 15 | 91 | 141 | 10160 | 13 | 7031 | 9 | 104 | 46 | 81 | 15 | 12 | 19 | 36 | 35 | 37 | 5099 | 11 | 10 | 13 | 497 | 3 | 2 | 4 | 111 | 897:1 | 6 | 48679 | 43944 | 53414 | 38024 | 39228 | 48161 | NaN | 51 | 38 | 3 | 2 | 5 | 51 | 14 | 10 | 18 | 20584 | 67 | 66 | 69 | 3461 | 12 | 10 | 14 | 76257 | 21.2 | 19.8 | 3022 | 4.0 | 344 | 0.5 | 1201 | 1.6 | 41 | 0.1 | 2188 | 2.9 | 68059 | 89.2 | 734 | 1 | 1 | 1 | 51.3 | 26041 | 34.7 |
| 3 | 47003 | Tennessee | Bedford | 74.8 | 74.0 | 75.6 | 74.7 | 85.8 | 74.1 | 799 | 489 | 454 | 524 | 495 | 281 | 512 | 34 | 69 | 48 | 97 | NaN | NaN | NaN | 36 | 8 | 6 | 11 | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 14 | 12 | 9 | 16 | 46 | 121 | 5690 | 12 | 2984 | 7 | 19 | 13 | 67 | 21 | 16 | 26 | 36 | 35 | 37 | 4627 | 17 | 14 | 19 | 591 | 5 | 3 | 6 | 98 | 1024:1 | 12 | 50904 | 45339 | 56469 | 35304 | 39554 | 48796 | NaN | 41 | 33 | NaN | NaN | NaN | 32 | 14 | 9 | 19 | 11631 | 68 | 66 | 71 | 2292 | 14 | 11 | 16 | 48117 | 25.5 | 15.1 | 3598 | 7.5 | 525 | 1.1 | 520 | 1.1 | 83 | 0.2 | 5822 | 12.1 | 37170 | 77.2 | 1463 | 3 | 2 | 4 | 50.9 | 25053 | 55.6 |
| 4 | 47005 | Tennessee | Benton | 72.6 | 71.2 | 74.1 | NaN | NaN | NaN | 409 | 606 | 542 | 671 | NaN | NaN | NaN | 10 | 79 | 38 | 145 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 15 | 16 | 14 | 11 | 19 | 13 | 94 | 2450 | 15 | 1082 | 7 | 17 | 35 | 38 | 34 | 24 | 46 | 37 | 36 | 38 | 1308 | 14 | 12 | 17 | 133 | 4 | 3 | 6 | 100 | 999:1 | NaN | 36034 | 31656 | 40412 | 20625 | 36635 | 34255 | NaN | 45 | 35 | NaN | NaN | NaN | 20 | 25 | 15 | 38 | 5066 | 76 | 72 | 79 | 794 | 13 | 10 | 16 | 15986 | 19.5 | 23.7 | 368 | 2.3 | 87 | 0.5 | 97 | 0.6 | 2 | 0.0 | 375 | 2.3 | 14851 | 92.9 | 36 | 0 | 0 | 1 | 50.9 | 12937 | 78.5 |
| 5 | 47007 | Tennessee | Bledsoe | 78.1 | 76.5 | 79.6 | NaN | NaN | NaN | 233 | 396 | 344 | 449 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 14 | 15 | 14 | 10 | 18 | 57 | 440 | 2200 | 16 | 211 | 2 | NaN | NaN | 13 | 13 | 7 | 23 | 37 | 36 | 38 | 1220 | 17 | 14 | 20 | 120 | 5 | 3 | 7 | 68 | 1472:1 | NaN | 38261 | 33484 | 43038 | NaN | NaN | NaN | NaN | 56 | 23 | NaN | NaN | NaN | 15 | 21 | 12 | 35 | 3533 | 76 | 71 | 81 | 373 | 9 | 5 | 12 | 14717 | 16.0 | 18.1 | 1026 | 7.0 | 81 | 0.6 | 35 | 0.2 | 5 | 0.0 | 339 | 2.3 | 13058 | 88.7 | 260 | 2 | 0 | 4 | 41.2 | 12876 | 100.0 |
| 6 | 47009 | Tennessee | Blount | 77.6 | 77.1 | 78.1 | 80.1 | 90.8 | 77.3 | 1925 | 391 | 372 | 409 | 465 | NaN | 397 | 57 | 54 | 41 | 70 | NaN | NaN | NaN | 49 | 5 | 4 | 7 | NaN | NaN | NaN | 13 | 13 | 14 | 13 | 13 | 13 | 15 | 11 | 18 | 118 | 109 | 14160 | 11 | 14303 | 12 | 121 | 31 | 106 | 12 | 10 | 14 | 33 | 32 | 35 | 9518 | 12 | 11 | 14 | 952 | 3 | 2 | 5 | 82 | 1214:1 | 6 | 51391 | 48123 | 54659 | 28322 | 31406 | 52333 | NaN | 63 | 36 | 2 | 1 | 3 | 88 | 14 | 11 | 17 | 37372 | 75 | 74 | 76 | 5387 | 11 | 10 | 13 | 129929 | 20.4 | 19.7 | 3800 | 2.9 | 545 | 0.4 | 1171 | 0.9 | 75 | 0.1 | 4285 | 3.3 | 118326 | 91.1 | 1042 | 1 | 1 | 1 | 51.5 | 40140 | 32.6 |
| 7 | 47011 | Tennessee | Bradley | 76.9 | 76.3 | 77.4 | 76.4 | 89.5 | 76.5 | 1591 | 424 | 402 | 445 | 460 | NaN | 438 | 48 | 52 | 38 | 69 | NaN | NaN | NaN | 55 | 7 | 5 | 9 | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 13 | 14 | 15 | 12 | 18 | 104 | 119 | 13560 | 13 | 11906 | 12 | 66 | 21 | 100 | 14 | 11 | 17 | 37 | 36 | 38 | 10118 | 16 | 14 | 18 | 1017 | 4 | 3 | 6 | 108 | 926:1 | 4 | 48663 | 44067 | 53259 | 34583 | 29098 | 48829 | NaN | 42 | 29 | 4 | 3 | 6 | 64 | 12 | 10 | 16 | 26120 | 66 | 64 | 68 | 4494 | 12 | 10 | 13 | 105560 | 22.0 | 16.8 | 5033 | 4.8 | 642 | 0.6 | 1240 | 1.2 | 120 | 0.1 | 6608 | 6.3 | 90607 | 85.8 | 1633 | 2 | 1 | 2 | 51.4 | 32630 | 33.0 |
| 8 | 47013 | Tennessee | Campbell | 72.0 | 71.1 | 72.9 | NaN | NaN | NaN | 1018 | 660 | 617 | 702 | NaN | NaN | NaN | 20 | 60 | 37 | 93 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 15 | 16 | 14 | 11 | 18 | 20 | 59 | 6200 | 16 | 4113 | 10 | 44 | 37 | 69 | 25 | 19 | 31 | 34 | 33 | 35 | 3374 | 15 | 12 | 17 | 262 | 3 | 2 | 4 | 136 | 734:1 | 8 | 40866 | 37365 | 44367 | 51641 | 56250 | 35344 | NaN | 68 | 45 | 4 | 2 | 7 | 24 | 12 | 8 | 18 | 10980 | 69 | 66 | 72 | 1528 | 10 | 9 | 12 | 39648 | 20.7 | 20.4 | 183 | 0.5 | 127 | 0.3 | 133 | 0.3 | 30 | 0.1 | 513 | 1.3 | 38233 | 96.4 | 26 | 0 | 0 | 0 | 51.0 | 22403 | 55.0 |
| 9 | 47015 | Tennessee | Cannon | 74.3 | 72.8 | 75.7 | NaN | NaN | NaN | 287 | 552 | 484 | 619 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 13 | 9 | 18 | 19 | 161 | 1700 | 12 | 146 | 1 | 15 | 36 | 28 | 29 | 19 | 42 | 34 | 33 | 36 | 1223 | 15 | 12 | 17 | 126 | 4 | 3 | 6 | 35 | 2843:1 | NaN | 51795 | 46635 | 56955 | NaN | 31875 | 47903 | NaN | 26 | 3 | 10 | 5 | 19 | 15 | 22 | 12 | 36 | 4015 | 74 | 70 | 78 | 394 | 8 | 5 | 11 | 14216 | 21.3 | 18.1 | 218 | 1.5 | 50 | 0.4 | 49 | 0.3 | 15 | 0.1 | 332 | 2.3 | 13352 | 93.9 | 25 | 0 | 0 | 1 | 50.3 | 11197 | 81.1 |
| 10 | 47017 | Tennessee | Carroll | 72.8 | 71.7 | 73.8 | 74.8 | NaN | 72.5 | 635 | 589 | 540 | 637 | 522 | NaN | 603 | 15 | 62 | 35 | 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 14 | 11 | 18 | 30 | 126 | 4410 | 16 | 964 | 3 | 10 | 12 | 49 | 25 | 18 | 33 | 36 | 35 | 37 | 1900 | 12 | 10 | 14 | 220 | 4 | 2 | 5 | 154 | 648:1 | 17 | 41492 | 37019 | 45965 | 28801 | 23345 | 39274 | NaN | 22 | 21 | NaN | NaN | NaN | 25 | 18 | 12 | 26 | 8204 | 72 | 70 | 75 | 1422 | 13 | 10 | 16 | 27860 | 21.3 | 20.2 | 2815 | 10.1 | 166 | 0.6 | 102 | 0.4 | 13 | 0.0 | 735 | 2.6 | 23573 | 84.6 | 26 | 0 | 0 | 0 | 51.2 | 23690 | 83.1 |
| 11 | 47019 | Tennessee | Carter | 76.1 | 75.3 | 76.9 | NaN | NaN | NaN | 1035 | 459 | 429 | 489 | NaN | NaN | NaN | 27 | 63 | 41 | 91 | NaN | NaN | NaN | 24 | 7 | 4 | 10 | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 15 | 16 | 15 | 12 | 19 | 63 | 129 | 8600 | 15 | 11750 | 20 | 52 | 31 | 45 | 11 | 8 | 15 | 36 | 35 | 37 | 4687 | 14 | 12 | 16 | 352 | 3 | 2 | 4 | 44 | 2260:1 | 9 | 39725 | 36626 | 42824 | NaN | 27976 | 34911 | NaN | 69 | 36 | NaN | NaN | NaN | 42 | 15 | 11 | 20 | 16656 | 70 | 68 | 72 | 3024 | 13 | 12 | 15 | 56488 | 18.8 | 21.4 | 830 | 1.5 | 158 | 0.3 | 230 | 0.4 | 15 | 0.0 | 1102 | 2.0 | 53510 | 94.7 | 98 | 0 | 0 | 0 | 51.0 | 23524 | 41.0 |
| 12 | 47021 | Tennessee | Cheatham | 74.0 | 73.2 | 74.9 | NaN | NaN | NaN | 729 | 503 | 466 | 541 | NaN | NaN | NaN | 20 | 54 | 33 | 84 | NaN | NaN | NaN | 22 | 7 | 4 | 11 | NaN | NaN | NaN | 13 | 12 | 13 | 13 | 12 | 13 | 13 | 10 | 17 | 58 | 174 | 4040 | 10 | 222 | 1 | 56 | 47 | 60 | 22 | 17 | 28 | 34 | 32 | 35 | 2889 | 12 | 10 | 13 | 336 | 4 | 2 | 5 | 77 | 1301:1 | 12 | 59103 | 54163 | 64043 | 52841 | 39005 | 57018 | NaN | 40 | 22 | 6 | 3 | 9 | 38 | 19 | 14 | 26 | 11599 | 79 | 77 | 81 | 1539 | 11 | 9 | 13 | 40330 | 22.7 | 14.4 | 690 | 1.7 | 212 | 0.5 | 186 | 0.5 | 28 | 0.1 | 1198 | 3.0 | 37451 | 92.9 | 33 | 0 | 0 | 0 | 50.4 | 32442 | 83.0 |
| 13 | 47023 | Tennessee | Chester | 77.5 | 76.2 | 78.7 | 79.5 | NaN | 77.2 | 250 | 403 | 351 | 455 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 13 | 9 | 17 | 8 | 54 | 2400 | 14 | 980 | 6 | 10 | 19 | 22 | 18 | 11 | 28 | 35 | 34 | 36 | 1403 | 15 | 12 | 17 | 149 | 4 | 2 | 5 | 82 | 1223:1 | NaN | 45261 | 39707 | 50815 | 24045 | 41447 | 49571 | NaN | 49 | 38 | NaN | NaN | NaN | 10 | 12 | 6 | 21 | 4500 | 75 | 71 | 79 | 636 | 11 | 7 | 15 | 17119 | 22.2 | 17.1 | 1543 | 9.0 | 87 | 0.5 | 99 | 0.6 | 5 | 0.0 | 446 | 2.6 | 14659 | 85.6 | 50 | 0 | 0 | 1 | 52.0 | 11177 | 65.2 |
| 14 | 47025 | Tennessee | Claiborne | 73.5 | 72.5 | 74.4 | NaN | NaN | NaN | 690 | 555 | 511 | 598 | NaN | NaN | NaN | 12 | 49 | 25 | 85 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 15 | 14 | 15 | 14 | 10 | 18 | 13 | 47 | 4780 | 15 | 3291 | 10 | 38 | 40 | 54 | 24 | 18 | 32 | 35 | 34 | 36 | 2268 | 12 | 10 | 14 | 211 | 3 | 2 | 4 | 158 | 632:1 | NaN | 37886 | 35037 | 40735 | 22895 | 26597 | 35941 | NaN | 69 | 36 | NaN | NaN | NaN | 38 | 24 | 17 | 33 | 9234 | 71 | 68 | 74 | 1782 | 15 | 12 | 18 | 31609 | 19.1 | 19.5 | 379 | 1.2 | 110 | 0.3 | 225 | 0.7 | 7 | 0.0 | 415 | 1.3 | 30094 | 95.2 | 105 | 0 | 0 | 1 | 51.1 | 23050 | 71.6 |
| 15 | 47027 | Tennessee | Clay | 72.1 | 69.6 | 74.5 | NaN | NaN | NaN | 199 | 645 | 546 | 745 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 18 | 17 | 18 | 17 | 16 | 17 | 14 | 10 | 18 | 7 | 105 | 1200 | 15 | 5 | 0 | 11 | 47 | 10 | 18 | 9 | 34 | 36 | 35 | 37 | 653 | 15 | 13 | 18 | 66 | 4 | 3 | 6 | 65 | 1541:1 | NaN | 34035 | 29524 | 38546 | NaN | NaN | NaN | NaN | 35 | 24 | NaN | NaN | NaN | 17 | 44 | 26 | 70 | 2359 | 74 | 66 | 82 | 290 | 10 | 5 | 15 | 7703 | 20.1 | 24.1 | 123 | 1.6 | 27 | 0.4 | 7 | 0.1 | 8 | 0.1 | 179 | 2.3 | 7280 | 94.5 | 50 | 1 | 0 | 2 | 50.6 | 7861 | 100.0 |
| 16 | 47029 | Tennessee | Cocke | 71.9 | 70.9 | 72.9 | NaN | NaN | NaN | 892 | 635 | 590 | 680 | NaN | NaN | NaN | 20 | 69 | 42 | 106 | NaN | NaN | NaN | 20 | 7 | 5 | 12 | NaN | NaN | NaN | 16 | 16 | 17 | 16 | 15 | 16 | 18 | 13 | 22 | 26 | 87 | 5790 | 16 | 4170 | 12 | 25 | 24 | 58 | 23 | 18 | 30 | 37 | 36 | 38 | 2792 | 14 | 11 | 16 | 231 | 3 | 2 | 4 | 84 | 1185:1 | 19 | 35788 | 31642 | 39934 | 24079 | 26071 | 32349 | NaN | 59 | 46 | 6 | 3 | 10 | 33 | 19 | 13 | 26 | 9964 | 68 | 65 | 71 | 1720 | 13 | 10 | 16 | 35556 | 20.4 | 20.7 | 718 | 2.0 | 212 | 0.6 | 156 | 0.4 | 25 | 0.1 | 857 | 2.4 | 33116 | 93.1 | 37 | 0 | 0 | 0 | 51.6 | 24083 | 67.5 |
| 17 | 47031 | Tennessee | Coffee | 74.3 | 73.5 | 75.0 | 72.2 | 86.1 | 74.1 | 1033 | 529 | 496 | 563 | 610 | NaN | 538 | 26 | 50 | 33 | 73 | NaN | NaN | NaN | 22 | 5 | 3 | 7 | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 13 | 10 | 16 | 46 | 102 | 6660 | 12 | 3899 | 7 | 46 | 28 | 76 | 20 | 16 | 25 | 36 | 34 | 37 | 4372 | 14 | 12 | 16 | 519 | 4 | 3 | 5 | 147 | 679:1 | 7 | 48188 | 43103 | 53273 | 34375 | 27447 | 47033 | NaN | 60 | 24 | 4 | 2 | 7 | 40 | 15 | 11 | 20 | 14625 | 68 | 65 | 70 | 2324 | 11 | 9 | 13 | 55034 | 24.0 | 17.2 | 1977 | 3.6 | 254 | 0.5 | 588 | 1.1 | 33 | 0.1 | 2328 | 4.2 | 48893 | 88.8 | 408 | 1 | 0 | 1 | 51.2 | 24967 | 47.3 |
| 18 | 47033 | Tennessee | Crockett | 75.5 | 74.2 | 76.8 | 76.4 | NaN | 74.7 | 244 | 447 | 389 | 505 | 470 | NaN | 471 | 10 | 71 | 34 | 131 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 16 | 16 | 15 | 15 | 15 | 13 | 9 | 17 | 14 | 116 | 1980 | 14 | 38 | 0 | NaN | NaN | 24 | 24 | 15 | 35 | 36 | 35 | 37 | 1449 | 17 | 15 | 20 | 184 | 5 | 3 | 7 | 76 | 1316:1 | NaN | 40480 | 35665 | 45295 | 30089 | 40473 | 42676 | NaN | 13 | 11 | NaN | NaN | NaN | 13 | 18 | 10 | 31 | 3770 | 70 | 66 | 73 | 558 | 11 | 8 | 14 | 14473 | 24.0 | 18.5 | 1983 | 13.7 | 90 | 0.6 | 46 | 0.3 | 4 | 0.0 | 1523 | 10.5 | 10698 | 73.9 | 228 | 2 | 1 | 2 | 52.3 | 9828 | 67.4 |
| 19 | 47035 | Tennessee | Cumberland | 76.9 | 76.1 | 77.7 | NaN | 86.5 | 76.7 | 1098 | 439 | 409 | 470 | NaN | NaN | NaN | 19 | 45 | 27 | 70 | NaN | NaN | NaN | 27 | 7 | 5 | 10 | NaN | NaN | NaN | 14 | 13 | 14 | 13 | 13 | 14 | 17 | 13 | 20 | 39 | 77 | 7040 | 12 | 4498 | 8 | 28 | 16 | 89 | 22 | 18 | 27 | 37 | 35 | 38 | 4607 | 15 | 13 | 17 | 442 | 4 | 3 | 5 | 93 | 1074:1 | 15 | 45118 | 41190 | 49046 | NaN | 38021 | 41051 | NaN | 80 | 40 | 4 | 2 | 6 | 63 | 22 | 17 | 28 | 19627 | 78 | 77 | 80 | 2599 | 11 | 9 | 12 | 59078 | 17.9 | 30.2 | 351 | 0.6 | 268 | 0.5 | 360 | 0.6 | 64 | 0.1 | 1766 | 3.0 | 55732 | 94.3 | 439 | 1 | 0 | 1 | 51.3 | 34132 | 60.9 |
| 20 | 47037 | Tennessee | Davidson | 77.0 | 76.8 | 77.2 | 74.4 | 85.7 | 77.6 | 8532 | 408 | 399 | 417 | 508 | 181 | 394 | 444 | 76 | 69 | 84 | 106 | 57 | 60 | 507 | 7 | 7 | 8 | 12 | 5 | 5 | 13 | 13 | 13 | 13 | 13 | 13 | 11 | 9 | 12 | 3444 | 607 | 103900 | 16 | 46009 | 7 | 618 | 30 | 479 | 10 | 9 | 11 | 39 | 38 | 40 | 66519 | 15 | 14 | 16 | 7257 | 5 | 4 | 6 | 203 | 493:1 | 6 | 58264 | 55596 | 60932 | 39046 | 41521 | 63080 | NaN | 48 | 41 | 10 | 9 | 11 | 556 | 16 | 15 | 18 | 148731 | 54 | 54 | 55 | 38762 | 15 | 14 | 15 | 691243 | 21.1 | 11.9 | 188619 | 27.3 | 3453 | 0.5 | 26343 | 3.8 | 784 | 0.1 | 71071 | 10.3 | 388640 | 56.2 | 30547 | 5 | 5 | 5 | 51.8 | 21382 | 3.4 |
| 21 | 47039 | Tennessee | Decatur | 75.4 | 73.8 | 77.0 | NaN | NaN | NaN | 231 | 484 | 416 | 552 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 15 | 11 | 19 | 12 | 121 | 1690 | 15 | 346 | 3 | 10 | 28 | 16 | 20 | 11 | 32 | 33 | 32 | 35 | 962 | 15 | 13 | 17 | 130 | 5 | 3 | 7 | 136 | 734:1 | 22 | 38988 | 34049 | 43927 | 19375 | 19423 | 38472 | NaN | 43 | 26 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 3473 | 74 | 70 | 77 | 566 | 13 | 8 | 17 | 11751 | 21.1 | 23.0 | 362 | 3.1 | 34 | 0.3 | 67 | 0.6 | 12 | 0.1 | 390 | 3.3 | 10769 | 91.6 | 0 | 0 | 0 | 1 | 50.8 | 11757 | 100.0 |
| 22 | 47041 | Tennessee | Dekalb | 73.5 | 72.2 | 74.8 | NaN | NaN | NaN | 386 | 536 | 480 | 593 | NaN | NaN | NaN | 14 | 82 | 45 | 137 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 14 | 10 | 18 | 34 | 210 | 2690 | 14 | 142 | 1 | 14 | 24 | 23 | 17 | 11 | 26 | 35 | 34 | 36 | 1826 | 16 | 14 | 18 | 195 | 5 | 3 | 6 | 60 | 1654:1 | NaN | 42080 | 37904 | 46256 | 47448 | 27090 | 41186 | NaN | 30 | 38 | NaN | NaN | NaN | 14 | 15 | 8 | 24 | 4896 | 67 | 63 | 70 | 663 | 10 | 7 | 12 | 19852 | 21.8 | 18.0 | 270 | 1.4 | 84 | 0.4 | 231 | 1.2 | 3 | 0.0 | 1594 | 8.0 | 17479 | 88.0 | 82 | 0 | 0 | 1 | 50.4 | 14673 | 78.4 |
| 23 | 47043 | Tennessee | Dickson | 74.2 | 73.4 | 75.0 | 69.6 | 84.7 | 74.2 | 947 | 515 | 481 | 549 | 780 | NaN | 509 | 30 | 62 | 42 | 88 | NaN | NaN | NaN | 22 | 5 | 3 | 8 | NaN | NaN | NaN | 13 | 13 | 14 | 14 | 13 | 14 | 13 | 9 | 17 | 62 | 145 | 6210 | 12 | 2577 | 5 | 48 | 31 | 96 | 27 | 22 | 33 | 36 | 34 | 37 | 4459 | 14 | 12 | 16 | 463 | 4 | 2 | 5 | 112 | 896:1 | 8 | 49518 | 44513 | 54523 | 29472 | 36079 | 48578 | NaN | 31 | 27 | 6 | 4 | 9 | 56 | 22 | 16 | 28 | 13571 | 71 | 69 | 73 | 1922 | 11 | 9 | 13 | 52853 | 23.4 | 15.7 | 2153 | 4.1 | 257 | 0.5 | 355 | 0.7 | 30 | 0.1 | 1892 | 3.6 | 47330 | 89.6 | 258 | 1 | 0 | 1 | 50.9 | 33650 | 67.8 |
| 24 | 47045 | Tennessee | Dyer | 73.8 | 72.9 | 74.7 | 71.9 | NaN | 73.9 | 769 | 559 | 518 | 600 | 697 | NaN | 552 | 25 | 69 | 45 | 102 | NaN | NaN | NaN | 34 | 10 | 7 | 14 | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 14 | 16 | 13 | 20 | 30 | 96 | 6050 | 16 | 5235 | 14 | 10 | 9 | 51 | 19 | 14 | 25 | 36 | 35 | 37 | 2735 | 12 | 10 | 15 | 320 | 3 | 2 | 5 | 123 | 814:1 | 13 | 44549 | 39694 | 49404 | 32348 | 48885 | 45462 | NaN | 45 | 42 | NaN | NaN | NaN | 25 | 13 | 9 | 20 | 9428 | 62 | 58 | 65 | 1492 | 10 | 8 | 12 | 37463 | 24.0 | 17.3 | 5221 | 13.9 | 150 | 0.4 | 295 | 0.8 | 12 | 0.0 | 1345 | 3.6 | 29947 | 79.9 | 194 | 1 | 0 | 1 | 51.8 | 16432 | 42.9 |
| 25 | 47047 | Tennessee | Fayette | 77.7 | 76.8 | 78.6 | 74.5 | NaN | 78.6 | 624 | 385 | 352 | 418 | 506 | NaN | 349 | 16 | 50 | 29 | 81 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 13 | 12 | 13 | 13 | 12 | 13 | 15 | 11 | 18 | 89 | 265 | 5690 | 15 | 932 | 2 | 15 | 13 | 44 | 16 | 12 | 22 | 35 | 34 | 36 | 2608 | 11 | 9 | 13 | 320 | 4 | 3 | 5 | 45 | 2224:1 | 9 | 60112 | 54846 | 65378 | 32285 | 22415 | 68108 | NaN | 33 | 31 | 7 | 4 | 10 | 33 | 17 | 12 | 24 | 12028 | 80 | 78 | 81 | 1533 | 11 | 9 | 13 | 40036 | 19.6 | 20.7 | 10963 | 27.4 | 138 | 0.3 | 279 | 0.7 | 16 | 0.0 | 1077 | 2.7 | 27255 | 68.1 | 149 | 0 | 0 | 1 | 50.7 | 30363 | 79.0 |
| 26 | 47049 | Tennessee | Fentress | 73.5 | 72.3 | 74.8 | NaN | NaN | NaN | 429 | 568 | 510 | 626 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 17 | 16 | 17 | 16 | 16 | 17 | 15 | 11 | 19 | 9 | 59 | 2660 | 15 | 19 | 0 | 10 | 18 | 31 | 25 | 17 | 35 | 33 | 32 | 34 | 1572 | 15 | 13 | 18 | 169 | 4 | 3 | 6 | 77 | 1295:1 | NaN | 32895 | 29057 | 36733 | NaN | 25197 | 33505 | NaN | NaN | 24 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 5580 | 76 | 72 | 79 | 817 | 12 | 8 | 16 | 18136 | 21.2 | 21.4 | 69 | 0.4 | 61 | 0.3 | 56 | 0.3 | 4 | 0.0 | 285 | 1.6 | 17489 | 96.4 | 9 | 0 | 0 | 1 | 51.1 | 17959 | 100.0 |
| 27 | 47051 | Tennessee | Franklin | 75.6 | 74.7 | 76.5 | 74.1 | NaN | 75.4 | 710 | 453 | 417 | 488 | 480 | NaN | 460 | 25 | 73 | 47 | 108 | NaN | NaN | NaN | 21 | 8 | 5 | 12 | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 14 | 11 | 17 | 21 | 59 | 5150 | 13 | 2906 | 7 | 28 | 22 | 60 | 21 | 16 | 27 | 35 | 34 | 36 | 3120 | 13 | 11 | 15 | 345 | 4 | 3 | 5 | 65 | 1543:1 | NaN | 49596 | 44363 | 54829 | 38500 | 35122 | 47948 | NaN | 38 | 30 | NaN | NaN | NaN | 27 | 13 | 9 | 19 | 12015 | 74 | 71 | 76 | 1551 | 10 | 8 | 12 | 41652 | 20.2 | 19.7 | 2106 | 5.1 | 181 | 0.4 | 385 | 0.9 | 34 | 0.1 | 1446 | 3.5 | 36834 | 88.4 | 435 | 1 | 0 | 2 | 51.4 | 28579 | 69.6 |
| 28 | 47053 | Tennessee | Gibson | 73.7 | 72.9 | 74.5 | 70.1 | NaN | 74.5 | 971 | 552 | 516 | 588 | 711 | NaN | 521 | 31 | 64 | 44 | 92 | 125 | NaN | 51 | 32 | 8 | 5 | 11 | NaN | NaN | NaN | 15 | 14 | 15 | 15 | 14 | 15 | 15 | 12 | 19 | 74 | 181 | 7840 | 16 | 3196 | 6 | 30 | 20 | 71 | 20 | 16 | 26 | 35 | 34 | 36 | 3294 | 12 | 10 | 13 | 411 | 3 | 2 | 4 | 88 | 1142:1 | NaN | 42859 | 38393 | 47325 | 25081 | NaN | 46924 | NaN | 43 | 40 | 7 | 4 | 10 | 45 | 18 | 13 | 24 | 13438 | 70 | 67 | 72 | 2086 | 11 | 9 | 14 | 49111 | 24.6 | 17.7 | 8981 | 18.3 | 154 | 0.3 | 143 | 0.3 | 12 | 0.0 | 1354 | 2.8 | 37791 | 77.0 | 101 | 0 | 0 | 1 | 52.0 | 23706 | 47.7 |
| 29 | 47055 | Tennessee | Giles | 74.9 | 73.8 | 76.0 | 74.2 | NaN | 74.8 | 535 | 481 | 438 | 525 | 468 | NaN | 490 | 19 | 78 | 47 | 121 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 13 | 14 | 15 | 11 | 18 | 39 | 157 | 3920 | 14 | 1492 | 5 | 23 | 26 | 62 | 30 | 23 | 39 | 35 | 34 | 36 | 2411 | 14 | 12 | 16 | 273 | 4 | 3 | 6 | 92 | 1089:1 | 6 | 47838 | 42472 | 53204 | 40238 | NaN | 44772 | NaN | 21 | 20 | NaN | NaN | NaN | 31 | 21 | 15 | 30 | 8086 | 70 | 67 | 72 | 937 | 9 | 6 | 11 | 29401 | 21.0 | 19.7 | 3088 | 10.5 | 116 | 0.4 | 140 | 0.5 | 13 | 0.0 | 687 | 2.3 | 24813 | 84.4 | 137 | 1 | 0 | 1 | 51.4 | 21744 | 73.7 |
| 30 | 47057 | Tennessee | Grainger | 74.2 | 73.0 | 75.4 | NaN | NaN | NaN | 476 | 518 | 468 | 568 | NaN | NaN | NaN | 18 | 94 | 56 | 149 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 14 | 10 | 19 | 17 | 87 | 2970 | 13 | 0 | 0 | 10 | 14 | 44 | 27 | 20 | 37 | 36 | 35 | 37 | 2033 | 15 | 12 | 17 | 217 | 4 | 3 | 6 | 43 | 2314:1 | NaN | 43190 | 38971 | 47409 | 10188 | 53100 | 40691 | NaN | NaN | 26 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 7061 | 77 | 76 | 79 | 768 | 9 | 6 | 11 | 23144 | 20.6 | 20.0 | 164 | 0.7 | 92 | 0.4 | 56 | 0.2 | 14 | 0.1 | 748 | 3.2 | 21869 | 94.5 | 202 | 1 | 0 | 2 | 49.6 | 22657 | 100.0 |
| 31 | 47059 | Tennessee | Greene | 74.5 | 73.9 | 75.2 | NaN | 94.2 | 74.2 | 1412 | 518 | 489 | 547 | 438 | NaN | 529 | 32 | 59 | 40 | 83 | NaN | NaN | NaN | 33 | 7 | 5 | 10 | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 15 | 12 | 18 | 51 | 86 | 9230 | 14 | 2503 | 4 | 43 | 21 | 92 | 19 | 15 | 24 | 38 | 37 | 39 | 5324 | 13 | 11 | 15 | 482 | 3 | 2 | 5 | 112 | 894:1 | 9 | 40145 | 35634 | 44656 | 26271 | 21282 | 38777 | NaN | 59 | 41 | 4 | 3 | 7 | 50 | 15 | 11 | 19 | 19864 | 73 | 71 | 74 | 2660 | 10 | 9 | 12 | 68808 | 19.7 | 21.3 | 1415 | 2.1 | 237 | 0.3 | 411 | 0.6 | 56 | 0.1 | 1954 | 2.8 | 64015 | 93.0 | 216 | 0 | 0 | 1 | 50.8 | 44874 | 65.2 |
| 32 | 47061 | Tennessee | Grundy | 71.6 | 70.0 | 73.1 | NaN | NaN | NaN | 332 | 635 | 562 | 708 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 17 | 16 | 17 | 16 | 16 | 17 | 16 | 12 | 21 | 8 | 70 | 2220 | 17 | 98 | 1 | NaN | NaN | 39 | 41 | 29 | 57 | 36 | 35 | 37 | 1321 | 18 | 15 | 20 | 121 | 4 | 3 | 6 | 82 | 1215:1 | NaN | 34454 | 30101 | 38807 | NaN | NaN | NaN | NaN | NaN | 20 | NaN | NaN | NaN | 14 | 21 | 11 | 35 | 3670 | 75 | 72 | 78 | 488 | 11 | 8 | 15 | 13361 | 21.9 | 20.8 | 77 | 0.6 | 88 | 0.7 | 50 | 0.4 | 1 | 0.0 | 177 | 1.3 | 12816 | 95.9 | 15 | 0 | 0 | 1 | 50.5 | 13703 | 100.0 |
| 33 | 47063 | Tennessee | Hamblen | 75.0 | 74.3 | 75.8 | 71.7 | 108.3 | 74.6 | 1180 | 507 | 477 | 537 | 689 | 172 | 525 | 30 | 51 | 34 | 72 | NaN | NaN | NaN | 33 | 6 | 4 | 9 | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 15 | 11 | 19 | 51 | 97 | 8420 | 13 | 11827 | 19 | 54 | 28 | 64 | 14 | 11 | 18 | 37 | 36 | 38 | 6194 | 17 | 14 | 19 | 621 | 4 | 3 | 5 | 157 | 636:1 | 6 | 44181 | 39930 | 48432 | 26779 | 21696 | 45593 | NaN | 51 | 38 | 3 | 2 | 5 | 47 | 15 | 11 | 20 | 16081 | 66 | 64 | 68 | 3084 | 13 | 11 | 16 | 64277 | 23.1 | 18.3 | 2417 | 3.8 | 546 | 0.8 | 620 | 1.0 | 162 | 0.3 | 7670 | 11.9 | 52283 | 81.3 | 1520 | 3 | 2 | 3 | 51.1 | 13680 | 21.9 |
| 34 | 47065 | Tennessee | Hamilton | 77.6 | 77.3 | 77.9 | 73.8 | 93.0 | 78.1 | 5112 | 401 | 390 | 412 | 561 | 123 | 382 | 183 | 61 | 52 | 70 | 104 | 37 | 50 | 214 | 7 | 6 | 8 | 13 | NaN | 6 | 13 | 12 | 13 | 13 | 13 | 13 | 13 | 12 | 15 | 888 | 297 | 50180 | 14 | 46488 | 14 | 215 | 20 | 264 | 11 | 9 | 12 | 37 | 36 | 37 | 26737 | 12 | 11 | 14 | 2204 | 3 | 2 | 4 | 167 | 599:1 | 6 | 52096 | 48522 | 55670 | 30035 | 38659 | 57241 | NaN | 61 | 54 | 9 | 7 | 10 | 287 | 16 | 14 | 18 | 89631 | 64 | 64 | 65 | 16980 | 13 | 12 | 13 | 361613 | 20.9 | 17.2 | 69540 | 19.2 | 1976 | 0.5 | 7632 | 2.1 | 531 | 0.1 | 20621 | 5.7 | 257150 | 71.1 | 4986 | 1 | 1 | 2 | 51.8 | 33721 | 10.0 |
| 35 | 47067 | Tennessee | Hancock | 70.6 | 68.4 | 72.8 | NaN | NaN | NaN | 167 | 664 | 556 | 773 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 17 | 16 | 17 | 16 | 16 | 17 | 14 | 10 | 19 | NaN | NaN | 1110 | 17 | 26 | 0 | NaN | NaN | 14 | 30 | 16 | 51 | 37 | 36 | 38 | 560 | 15 | 12 | 17 | 46 | 3 | 2 | 5 | 167 | 600:1 | NaN | 29689 | 25790 | 33588 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2094 | 77 | 72 | 82 | 190 | 8 | 4 | 12 | 6600 | 21.0 | 20.7 | 33 | 0.5 | 23 | 0.3 | 13 | 0.2 | 3 | 0.0 | 34 | 0.5 | 6400 | 97.0 | 29 | 0 | 0 | 2 | 50.8 | 6819 | 100.0 |
| 36 | 47069 | Tennessee | Hardeman | 74.3 | 73.2 | 75.4 | 74.0 | NaN | 74.1 | 501 | 528 | 480 | 576 | 551 | NaN | 532 | 15 | 74 | 41 | 122 | NaN | NaN | NaN | 20 | 11 | 7 | 17 | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 14 | 15 | 15 | 12 | 19 | 39 | 176 | 5290 | 20 | 5218 | 19 | 10 | 13 | 40 | 22 | 16 | 30 | 41 | 40 | 42 | 1728 | 14 | 12 | 16 | 172 | 3 | 2 | 5 | 67 | 1497:1 | 19 | 38426 | 34537 | 42315 | 30413 | 127813 | 40195 | NaN | 44 | 42 | 12 | 8 | 18 | 22 | 17 | 11 | 26 | 6039 | 70 | 66 | 73 | 1102 | 13 | 10 | 16 | 25447 | 19.7 | 17.7 | 10600 | 41.7 | 81 | 0.3 | 184 | 0.7 | 3 | 0.0 | 454 | 1.8 | 13855 | 54.4 | 55 | 0 | 0 | 1 | 45.2 | 21859 | 80.2 |
| 37 | 47071 | Tennessee | Hardin | 73.0 | 71.9 | 74.2 | NaN | NaN | NaN | 622 | 604 | 553 | 655 | NaN | NaN | NaN | 15 | 70 | 39 | 116 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 14 | 10 | 17 | 29 | 132 | 3750 | 15 | 1854 | 7 | 24 | 31 | 51 | 28 | 21 | 37 | 33 | 32 | 34 | 2102 | 14 | 12 | 17 | 208 | 4 | 3 | 5 | 120 | 834:1 | NaN | 39318 | 34768 | 43868 | 21146 | 21771 | 40201 | NaN | 41 | 37 | 6 | 3 | 11 | 29 | 22 | 15 | 32 | 7596 | 75 | 72 | 78 | 923 | 10 | 7 | 13 | 25846 | 20.6 | 22.6 | 852 | 3.3 | 158 | 0.6 | 144 | 0.6 | 8 | 0.0 | 683 | 2.6 | 23688 | 91.7 | 143 | 1 | 0 | 1 | 51.3 | 17679 | 67.9 |
| 38 | 47073 | Tennessee | Hawkins | 74.7 | 73.9 | 75.5 | NaN | NaN | NaN | 1129 | 506 | 474 | 537 | NaN | NaN | NaN | 29 | 62 | 42 | 89 | NaN | NaN | NaN | 42 | 11 | 8 | 15 | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 15 | 12 | 18 | 36 | 74 | 7630 | 14 | 3992 | 7 | 46 | 27 | 77 | 19 | 15 | 24 | 35 | 34 | 36 | 4395 | 13 | 11 | 15 | 380 | 3 | 2 | 4 | 66 | 1526:1 | 7 | 41397 | 37494 | 45300 | 39107 | 78333 | 38638 | NaN | 54 | 42 | 4 | 2 | 6 | 42 | 15 | 11 | 20 | 17302 | 74 | 72 | 76 | 2639 | 12 | 10 | 14 | 56459 | 20.2 | 20.5 | 826 | 1.5 | 198 | 0.4 | 266 | 0.5 | 13 | 0.0 | 919 | 1.6 | 53640 | 95.0 | 149 | 0 | 0 | 1 | 50.9 | 32884 | 57.9 |
| 39 | 47075 | Tennessee | Haywood | 75.3 | 73.9 | 76.7 | 74.0 | NaN | 75.9 | 325 | 488 | 433 | 544 | 525 | NaN | 480 | 15 | 90 | 51 | 149 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 14 | 15 | 14 | 11 | 18 | 90 | 597 | 3870 | 21 | 1561 | 8 | NaN | NaN | 25 | 20 | 13 | 29 | 39 | 38 | 40 | 1382 | 13 | 11 | 15 | 139 | 3 | 2 | 5 | 74 | 1352:1 | NaN | 34556 | 30953 | 38159 | 27806 | 53558 | 47152 | NaN | 19 | 18 | NaN | NaN | NaN | 12 | 13 | 7 | 23 | 4258 | 60 | 56 | 64 | 974 | 15 | 12 | 18 | 17573 | 22.6 | 18.1 | 8804 | 50.1 | 72 | 0.4 | 50 | 0.3 | 5 | 0.0 | 781 | 4.4 | 7716 | 43.9 | 94 | 1 | 0 | 1 | 53.1 | 8908 | 47.4 |
| 40 | 47077 | Tennessee | Henderson | 73.4 | 72.3 | 74.5 | 71.3 | NaN | 73.5 | 578 | 565 | 517 | 613 | 720 | NaN | 556 | 18 | 70 | 41 | 110 | NaN | NaN | NaN | 20 | 9 | 6 | 14 | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 15 | 12 | 19 | 22 | 94 | 4370 | 16 | 1233 | 4 | 13 | 16 | 53 | 27 | 20 | 35 | 38 | 37 | 39 | 2277 | 14 | 12 | 16 | 256 | 4 | 3 | 5 | 76 | 1321:1 | NaN | 43806 | 38310 | 49302 | 21176 | NaN | 46200 | NaN | 33 | 31 | NaN | NaN | NaN | 22 | 16 | 10 | 24 | 7831 | 72 | 68 | 76 | 1091 | 11 | 8 | 14 | 27751 | 22.9 | 18.2 | 2110 | 7.6 | 89 | 0.3 | 100 | 0.4 | 5 | 0.0 | 607 | 2.2 | 24364 | 87.8 | 87 | 0 | 0 | 1 | 51.6 | 21209 | 76.4 |
| 41 | 47079 | Tennessee | Henry | 74.5 | 73.5 | 75.5 | 71.7 | NaN | 74.4 | 696 | 512 | 471 | 553 | 647 | NaN | 511 | 22 | 82 | 51 | 124 | NaN | NaN | NaN | 20 | 9 | 5 | 13 | NaN | NaN | NaN | 15 | 15 | 16 | 14 | 14 | 15 | 15 | 12 | 18 | 31 | 113 | 4700 | 15 | 2600 | 8 | 11 | 11 | 51 | 23 | 17 | 30 | 35 | 34 | 37 | 2626 | 15 | 12 | 17 | 263 | 4 | 3 | 5 | 99 | 1014:1 | NaN | 41756 | 37952 | 45560 | 32574 | 27688 | 41079 | NaN | 52 | 47 | 6 | 3 | 10 | 43 | 27 | 19 | 36 | 10173 | 75 | 73 | 78 | 1277 | 10 | 8 | 12 | 32450 | 20.8 | 22.7 | 2476 | 7.6 | 143 | 0.4 | 154 | 0.5 | 17 | 0.1 | 853 | 2.6 | 28299 | 87.2 | 107 | 0 | 0 | 1 | 51.6 | 21612 | 66.8 |
| 42 | 47081 | Tennessee | Hickman | 74.4 | 73.3 | 75.5 | NaN | NaN | NaN | 474 | 523 | 474 | 571 | NaN | NaN | NaN | 13 | 61 | 33 | 105 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 14 | 14 | 15 | 13 | 9 | 17 | 20 | 97 | 3430 | 14 | 1270 | 5 | 17 | 23 | 53 | 31 | 23 | 41 | 36 | 35 | 38 | 2140 | 15 | 13 | 18 | 254 | 5 | 3 | 6 | 36 | 2763:1 | 13 | 42824 | 38330 | 47318 | NaN | 34697 | 40162 | NaN | 30 | 22 | NaN | NaN | NaN | 14 | 12 | 6 | 19 | 6998 | 78 | 75 | 82 | 1068 | 13 | 9 | 16 | 24864 | 21.2 | 17.1 | 1192 | 4.8 | 157 | 0.6 | 88 | 0.4 | 7 | 0.0 | 640 | 2.6 | 22457 | 90.3 | 60 | 0 | 0 | 1 | 47.4 | 24690 | 100.0 |
| 43 | 47083 | Tennessee | Houston | 74.2 | 72.3 | 76.0 | NaN | NaN | NaN | 162 | 522 | 435 | 608 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 15 | 16 | 14 | 11 | 19 | NaN | NaN | 1230 | 15 | 116 | 1 | NaN | NaN | 12 | 21 | 11 | 36 | 36 | 35 | 38 | 667 | 14 | 12 | 17 | 76 | 4 | 3 | 6 | 73 | 1369:1 | NaN | 42018 | 38284 | 45752 | 27583 | NaN | 42586 | NaN | 52 | 37 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2315 | 77 | 73 | 81 | 302 | 11 | 6 | 15 | 8213 | 21.8 | 20.4 | 236 | 2.9 | 31 | 0.4 | 48 | 0.6 | 6 | 0.1 | 191 | 2.3 | 7554 | 92.0 | 18 | 0 | 0 | 1 | 50.9 | 8426 | 100.0 |
| 44 | 47085 | Tennessee | Humphreys | 73.7 | 72.3 | 75.1 | NaN | NaN | NaN | 373 | 525 | 468 | 581 | NaN | NaN | NaN | 12 | 75 | 39 | 131 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 13 | 14 | 13 | 13 | 14 | 14 | 10 | 19 | 12 | 78 | 2450 | 14 | 491 | 3 | 15 | 27 | 34 | 27 | 18 | 37 | 35 | 34 | 36 | 1286 | 12 | 10 | 14 | 150 | 4 | 2 | 5 | 81 | 1232:1 | NaN | 45866 | 40144 | 51588 | 25759 | 43110 | 41172 | NaN | 40 | 25 | NaN | NaN | NaN | 20 | 22 | 13 | 34 | 5432 | 77 | 73 | 80 | 713 | 11 | 7 | 14 | 18484 | 21.8 | 19.7 | 490 | 2.7 | 122 | 0.7 | 82 | 0.4 | 8 | 0.0 | 473 | 2.6 | 17098 | 92.5 | 13 | 0 | 0 | 1 | 50.3 | 15292 | 82.5 |
| 45 | 47087 | Tennessee | Jackson | 74.6 | 72.8 | 76.3 | NaN | NaN | NaN | 261 | 513 | 444 | 581 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 17 | 16 | 18 | 16 | 16 | 17 | 15 | 11 | 19 | 13 | 129 | 1800 | 16 | 1 | 0 | 11 | 32 | 18 | 22 | 13 | 35 | 37 | 35 | 38 | 1060 | 16 | 13 | 18 | 116 | 5 | 3 | 7 | 9 | 11677:1 | NaN | 36815 | 32535 | 41095 | NaN | NaN | NaN | NaN | NaN | 58 | NaN | NaN | NaN | 10 | 17 | 8 | 32 | 3470 | 76 | 72 | 80 | 489 | 12 | 8 | 16 | 11677 | 18.2 | 22.1 | 56 | 0.5 | 77 | 0.7 | 17 | 0.1 | 4 | 0.0 | 248 | 2.1 | 11138 | 95.4 | 8 | 0 | 0 | 1 | 50.2 | 11638 | 100.0 |
| 46 | 47089 | Tennessee | Jefferson | 75.6 | 74.8 | 76.4 | NaN | 78.9 | 75.5 | 946 | 454 | 423 | 485 | 722 | NaN | 455 | 24 | 55 | 36 | 82 | NaN | NaN | NaN | 24 | 7 | 4 | 10 | NaN | NaN | NaN | 14 | 13 | 14 | 13 | 13 | 14 | 14 | 10 | 18 | 47 | 103 | 6420 | 12 | 1312 | 3 | 22 | 14 | 58 | 16 | 12 | 20 | 33 | 32 | 34 | 4181 | 13 | 12 | 15 | 372 | 3 | 2 | 4 | 82 | 1223:1 | NaN | 45556 | 41053 | 50059 | 34870 | 53438 | 45906 | NaN | 54 | 41 | 4 | 3 | 7 | 26 | 10 | 6 | 14 | 14751 | 73 | 71 | 76 | 1878 | 10 | 8 | 12 | 53804 | 19.9 | 19.6 | 1054 | 2.0 | 245 | 0.5 | 319 | 0.6 | 29 | 0.1 | 1971 | 3.7 | 49604 | 92.2 | 484 | 1 | 1 | 1 | 50.9 | 30581 | 59.5 |
| 47 | 47091 | Tennessee | Johnson | 73.2 | 71.6 | 74.9 | NaN | NaN | NaN | 396 | 560 | 500 | 620 | NaN | NaN | NaN | 14 | 114 | 63 | 192 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 16 | 17 | 15 | 15 | 16 | 14 | 10 | 17 | 30 | 191 | 2780 | 16 | 873 | 5 | NaN | NaN | 27 | 22 | 14 | 31 | 37 | 36 | 38 | 1371 | 15 | 13 | 17 | 121 | 4 | 3 | 5 | 130 | 769:1 | NaN | 36331 | 31875 | 40787 | 70804 | 21051 | 33144 | NaN | 45 | 19 | NaN | NaN | NaN | 20 | 22 | 14 | 35 | 5305 | 76 | 74 | 79 | 639 | 10 | 7 | 13 | 17691 | 16.8 | 22.5 | 403 | 2.3 | 53 | 0.3 | 41 | 0.2 | 10 | 0.1 | 379 | 2.1 | 16644 | 94.1 | 51 | 0 | 0 | 1 | 46.0 | 15546 | 85.2 |
| 48 | 47093 | Tennessee | Knox | 76.7 | 76.4 | 77.0 | 71.8 | 105.8 | 76.9 | 6566 | 424 | 414 | 435 | 628 | 200 | 416 | 211 | 55 | 47 | 62 | 103 | 72 | 46 | 217 | 6 | 5 | 7 | 11 | 8 | 5 | 13 | 13 | 14 | 14 | 13 | 14 | 12 | 10 | 13 | 729 | 191 | 59550 | 13 | 49168 | 11 | 569 | 42 | 394 | 13 | 11 | 14 | 34 | 33 | 35 | 32100 | 11 | 10 | 13 | 3019 | 3 | 2 | 4 | 187 | 535:1 | 6 | 55299 | 53268 | 57330 | 29034 | 36594 | 56286 | NaN | 56 | 42 | 5 | 4 | 6 | 319 | 14 | 13 | 16 | 116893 | 64 | 63 | 65 | 21759 | 12 | 12 | 13 | 461860 | 21.2 | 15.4 | 40297 | 8.7 | 1562 | 0.3 | 10754 | 2.3 | 521 | 0.1 | 19745 | 4.3 | 380672 | 82.4 | 5461 | 1 | 1 | 1 | 51.4 | 47205 | 10.9 |
| 49 | 47095 | Tennessee | Lake | 71.9 | 69.9 | 73.9 | 81.5 | NaN | 70.5 | 172 | 659 | 559 | 760 | 529 | NaN | 712 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 16 | 17 | 15 | 14 | 15 | 12 | 9 | 16 | 45 | 666 | 1690 | 22 | 8 | 0 | NaN | NaN | 10 | 19 | 9 | 34 | 39 | 38 | 40 | 419 | 14 | 12 | 16 | 39 | 4 | 2 | 5 | 121 | 830:1 | NaN | 31144 | 26986 | 35302 | 19917 | 23523 | 40691 | NaN | 16 | 14 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1284 | 59 | 56 | 63 | 236 | 12 | 6 | 18 | 7468 | 14.7 | 15.6 | 2139 | 28.6 | 35 | 0.5 | 14 | 0.2 | 2 | 0.0 | 171 | 2.3 | 4975 | 66.6 | 16 | 0 | 0 | 1 | 36.1 | 7832 | 100.0 |
| 50 | 47097 | Tennessee | Lauderdale | 73.1 | 72.0 | 74.3 | 71.4 | NaN | 73.9 | 513 | 559 | 510 | 609 | 600 | NaN | 545 | 25 | 102 | 66 | 150 | 135 | NaN | 79 | 27 | 12 | 8 | 18 | NaN | NaN | NaN | 17 | 16 | 17 | 15 | 15 | 16 | 17 | 13 | 21 | 84 | 370 | 5880 | 22 | 1563 | 6 | 14 | 18 | 54 | 28 | 21 | 37 | 40 | 39 | 41 | 2076 | 15 | 12 | 17 | 198 | 3 | 2 | 4 | 67 | 1487:1 | 12 | 38718 | 36390 | 41046 | 24753 | NaN | 42131 | NaN | 41 | 40 | 11 | 7 | 17 | 25 | 19 | 12 | 28 | 5590 | 57 | 55 | 59 | 1614 | 18 | 14 | 21 | 25274 | 23.8 | 15.7 | 8377 | 33.1 | 186 | 0.7 | 199 | 0.8 | 3 | 0.0 | 622 | 2.5 | 15579 | 61.6 | 147 | 1 | 0 | 1 | 50.4 | 16317 | 58.7 |
| 51 | 47099 | Tennessee | Lawrence | 74.3 | 73.5 | 75.1 | NaN | NaN | NaN | 809 | 520 | 483 | 558 | NaN | NaN | NaN | 39 | 91 | 65 | 124 | NaN | NaN | NaN | 30 | 8 | 5 | 11 | NaN | NaN | NaN | 15 | 14 | 15 | 15 | 14 | 15 | 15 | 11 | 18 | 31 | 89 | 5760 | 14 | 1200 | 3 | 25 | 19 | 54 | 18 | 14 | 24 | 37 | 36 | 38 | 3634 | 15 | 13 | 17 | 413 | 4 | 3 | 5 | 113 | 886:1 | 13 | 41505 | 37412 | 45598 | 26932 | 52366 | 41499 | NaN | 66 | 45 | 3 | 2 | 6 | 29 | 14 | 9 | 20 | 11887 | 74 | 71 | 76 | 1641 | 11 | 9 | 13 | 43396 | 25.1 | 17.6 | 718 | 1.7 | 196 | 0.5 | 233 | 0.5 | 10 | 0.0 | 949 | 2.2 | 40685 | 93.8 | 516 | 1 | 0 | 2 | 50.9 | 31769 | 75.9 |
| 52 | 47101 | Tennessee | Lewis | 74.6 | 72.8 | 76.4 | NaN | NaN | NaN | 244 | 532 | 460 | 604 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 15 | 11 | 20 | 9 | 89 | 1650 | 14 | 221 | 2 | NaN | NaN | 14 | 17 | 9 | 28 | 35 | 33 | 36 | 996 | 15 | 12 | 17 | 102 | 4 | 2 | 5 | 58 | 1719:1 | NaN | 37959 | 33273 | 42645 | NaN | 51927 | 37441 | NaN | NaN | 27 | NaN | NaN | NaN | 24 | 40 | 26 | 60 | 3674 | 79 | 75 | 82 | 215 | 5 | 2 | 8 | 12035 | 21.4 | 20.7 | 234 | 1.9 | 59 | 0.5 | 68 | 0.6 | 6 | 0.0 | 271 | 2.3 | 11252 | 93.5 | 177 | 2 | 0 | 3 | 51.3 | 8536 | 70.2 |
| 53 | 47103 | Tennessee | Lincoln | 74.9 | 73.9 | 76.0 | 71.3 | NaN | 74.8 | 604 | 478 | 437 | 519 | 604 | NaN | 486 | 18 | 60 | 36 | 95 | NaN | NaN | NaN | 21 | 8 | 5 | 13 | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 14 | 11 | 18 | 26 | 92 | 4370 | 13 | 2119 | 6 | 16 | 16 | 51 | 22 | 16 | 29 | 39 | 38 | 41 | 2704 | 14 | 12 | 16 | 333 | 4 | 3 | 6 | 62 | 1607:1 | NaN | 49295 | 43627 | 54963 | 28417 | 32091 | 43527 | NaN | 47 | 35 | NaN | NaN | NaN | 22 | 13 | 8 | 20 | 9904 | 73 | 69 | 76 | 1550 | 12 | 9 | 14 | 33751 | 22.1 | 19.2 | 2285 | 6.8 | 280 | 0.8 | 167 | 0.5 | 54 | 0.2 | 1161 | 3.4 | 29327 | 86.9 | 123 | 0 | 0 | 1 | 51.0 | 24183 | 72.5 |
| 54 | 47105 | Tennessee | Loudon | 76.6 | 75.7 | 77.4 | NaN | 107.2 | 76.2 | 935 | 434 | 402 | 466 | NaN | NaN | NaN | 25 | 62 | 40 | 91 | NaN | NaN | NaN | 24 | 6 | 4 | 9 | NaN | NaN | NaN | 13 | 13 | 14 | 13 | 12 | 13 | 13 | 10 | 17 | 49 | 112 | 5070 | 10 | 5555 | 11 | 46 | 30 | 52 | 15 | 11 | 19 | 33 | 32 | 34 | 4263 | 15 | 13 | 17 | 477 | 5 | 3 | 6 | 69 | 1449:1 | NaN | 57641 | 52948 | 62334 | 30761 | 44917 | 56574 | NaN | 55 | 42 | NaN | NaN | NaN | 31 | 12 | 8 | 17 | 15282 | 76 | 74 | 78 | 1770 | 9 | 7 | 11 | 52152 | 19.6 | 25.9 | 657 | 1.3 | 306 | 0.6 | 436 | 0.8 | 112 | 0.2 | 4479 | 8.6 | 45853 | 87.9 | 1351 | 3 | 2 | 4 | 50.8 | 19720 | 40.6 |
| 55 | 47107 | Tennessee | Mcminn | 74.7 | 73.9 | 75.5 | 72.1 | 78.4 | 74.6 | 1017 | 508 | 475 | 541 | 647 | NaN | 512 | 23 | 51 | 32 | 76 | NaN | NaN | NaN | 21 | 5 | 3 | 8 | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 14 | 11 | 17 | 53 | 118 | 7160 | 14 | 2657 | 5 | 39 | 25 | 69 | 19 | 15 | 24 | 36 | 35 | 37 | 3941 | 13 | 11 | 15 | 456 | 4 | 3 | 5 | 91 | 1102:1 | 8 | 39860 | 36165 | 43555 | 21875 | 25134 | 41469 | NaN | 45 | 32 | 6 | 4 | 9 | 43 | 16 | 12 | 22 | 15115 | 74 | 73 | 76 | 2708 | 14 | 11 | 16 | 52877 | 21.3 | 19.5 | 1960 | 3.7 | 273 | 0.5 | 384 | 0.7 | 21 | 0.0 | 2166 | 4.1 | 47146 | 89.2 | 283 | 1 | 0 | 1 | 51.2 | 31538 | 60.3 |
| 56 | 47109 | Tennessee | Mcnairy | 73.3 | 72.2 | 74.3 | 78.5 | NaN | 72.9 | 587 | 582 | 532 | 632 | 486 | NaN | 595 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 16 | 17 | 16 | 15 | 16 | 15 | 12 | 19 | 16 | 73 | 4160 | 16 | 1315 | 5 | 20 | 26 | 48 | 26 | 19 | 35 | 36 | 35 | 37 | 2214 | 15 | 13 | 17 | 224 | 4 | 2 | 5 | 69 | 1445:1 | 15 | 39407 | 35013 | 43801 | 22290 | NaN | 35421 | NaN | 26 | 17 | NaN | NaN | NaN | 28 | 22 | 14 | 31 | 7428 | 74 | 71 | 76 | 1008 | 11 | 8 | 14 | 26004 | 22.1 | 20.3 | 1545 | 5.9 | 97 | 0.4 | 81 | 0.3 | 5 | 0.0 | 540 | 2.1 | 23372 | 89.9 | 52 | 0 | 0 | 1 | 50.7 | 22235 | 85.3 |
| 57 | 47111 | Tennessee | Macon | 74.0 | 72.8 | 75.1 | NaN | NaN | NaN | 454 | 543 | 491 | 594 | NaN | NaN | NaN | 15 | 65 | 36 | 107 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 15 | 11 | 19 | 10 | 53 | 2790 | 12 | 412 | 2 | 13 | 18 | 42 | 26 | 19 | 35 | 37 | 36 | 38 | 2562 | 19 | 16 | 21 | 273 | 5 | 3 | 6 | 58 | 1720:1 | NaN | 41266 | 36222 | 46310 | NaN | 28634 | 36009 | NaN | NaN | 26 | NaN | NaN | NaN | 27 | 23 | 15 | 34 | 6723 | 73 | 70 | 76 | 992 | 11 | 8 | 15 | 24079 | 24.8 | 15.4 | 197 | 0.8 | 177 | 0.7 | 289 | 1.2 | 10 | 0.0 | 1355 | 5.6 | 21929 | 91.1 | 309 | 1 | 0 | 2 | 51.5 | 17703 | 79.6 |
| 58 | 47113 | Tennessee | Madison | 75.5 | 74.9 | 76.0 | 72.9 | NaN | 76.5 | 1576 | 466 | 442 | 490 | 588 | NaN | 416 | 75 | 84 | 66 | 105 | 111 | NaN | 60 | 80 | 9 | 7 | 11 | 13 | NaN | 5 | 14 | 14 | 14 | 14 | 13 | 14 | 13 | 11 | 15 | 217 | 266 | 17900 | 18 | 10428 | 11 | 39 | 13 | 102 | 15 | 12 | 18 | 37 | 37 | 38 | 6342 | 11 | 10 | 13 | 841 | 4 | 2 | 5 | 182 | 549:1 | 11 | 46424 | 42014 | 50834 | 31934 | 30649 | 55432 | NaN | 41 | 39 | 12 | 9 | 15 | 89 | 18 | 15 | 22 | 23511 | 63 | 62 | 64 | 5991 | 17 | 15 | 19 | 97643 | 22.5 | 16.6 | 36591 | 37.5 | 324 | 0.3 | 1115 | 1.1 | 46 | 0.0 | 3773 | 3.9 | 54550 | 55.9 | 462 | 1 | 0 | 1 | 52.7 | 25386 | 25.8 |
| 59 | 47115 | Tennessee | Marion | 74.1 | 73.1 | 75.1 | NaN | NaN | NaN | 641 | 563 | 517 | 610 | 695 | NaN | 566 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 17 | 13 | 21 | 24 | 99 | 3990 | 14 | 1092 | 4 | 18 | 21 | 48 | 24 | 18 | 32 | 37 | 35 | 38 | 2034 | 12 | 10 | 14 | 213 | 3 | 2 | 4 | 60 | 1672:1 | NaN | 47331 | 43107 | 51555 | 41513 | NaN | 46903 | NaN | 41 | 19 | NaN | NaN | NaN | 22 | 16 | 10 | 23 | 8511 | 75 | 72 | 77 | 1223 | 12 | 9 | 14 | 28425 | 21.3 | 19.5 | 1109 | 3.9 | 131 | 0.5 | 178 | 0.6 | 7 | 0.0 | 504 | 1.8 | 26068 | 91.7 | 3 | 0 | 0 | 0 | 51.1 | 21747 | 77.0 |
| 60 | 47117 | Tennessee | Marshall | 75.1 | 74.1 | 76.0 | 70.2 | NaN | 75.1 | 570 | 482 | 441 | 522 | 702 | NaN | 477 | 21 | 70 | 43 | 107 | NaN | NaN | NaN | 24 | 10 | 6 | 14 | NaN | NaN | NaN | 13 | 13 | 14 | 13 | 13 | 14 | 13 | 9 | 16 | 35 | 133 | 3840 | 12 | 2380 | 8 | 29 | 30 | 38 | 17 | 12 | 24 | 35 | 34 | 36 | 2713 | 14 | 12 | 16 | 341 | 4 | 3 | 6 | 79 | 1267:1 | NaN | 52415 | 46244 | 58586 | 31367 | 38859 | 48890 | NaN | 42 | 39 | 6 | 3 | 10 | 21 | 13 | 8 | 20 | 8608 | 72 | 69 | 75 | 1260 | 11 | 8 | 13 | 32931 | 23.4 | 15.9 | 2156 | 6.5 | 143 | 0.4 | 222 | 0.7 | 30 | 0.1 | 1693 | 5.1 | 28187 | 85.6 | 274 | 1 | 0 | 2 | 50.8 | 20153 | 65.8 |
| 61 | 47119 | Tennessee | Maury | 76.2 | 75.6 | 76.8 | 74.4 | 95.1 | 76.0 | 1369 | 423 | 399 | 446 | 523 | 238 | 422 | 46 | 55 | 40 | 73 | NaN | NaN | NaN | 47 | 6 | 4 | 8 | NaN | NaN | NaN | 14 | 13 | 14 | 13 | 13 | 14 | 11 | 9 | 14 | 115 | 158 | 10880 | 13 | 5762 | 7 | 51 | 19 | 91 | 15 | 12 | 19 | 36 | 35 | 37 | 6318 | 12 | 10 | 13 | 866 | 4 | 3 | 5 | 122 | 823:1 | 10 | 56999 | 52276 | 61722 | 38190 | 47721 | 53957 | NaN | 35 | 29 | 4 | 3 | 6 | 60 | 14 | 10 | 18 | 22891 | 69 | 67 | 70 | 3790 | 12 | 10 | 13 | 92163 | 23.5 | 15.5 | 10789 | 11.7 | 454 | 0.5 | 878 | 1.0 | 50 | 0.1 | 5383 | 5.8 | 73119 | 79.3 | 653 | 1 | 0 | 1 | 51.8 | 33672 | 41.6 |
| 62 | 47121 | Tennessee | Meigs | 72.5 | 70.8 | 74.2 | NaN | NaN | NaN | 291 | 604 | 529 | 678 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 14 | 11 | 19 | 10 | 98 | 1640 | 14 | 71 | 1 | 18 | 50 | 33 | 40 | 28 | 56 | 35 | 34 | 37 | 1015 | 15 | 12 | 17 | 117 | 4 | 3 | 6 | 41 | 2414:1 | NaN | 45695 | 41048 | 50342 | NaN | NaN | NaN | NaN | NaN | 58 | NaN | NaN | NaN | 11 | 19 | 9 | 33 | 3816 | 79 | 76 | 82 | 547 | 12 | 8 | 16 | 12068 | 20.9 | 20.7 | 174 | 1.4 | 111 | 0.9 | 44 | 0.4 | 4 | 0.0 | 242 | 2.0 | 11383 | 94.3 | 43 | 0 | 0 | 1 | 50.3 | 11753 | 100.0 |
| 63 | 47123 | Tennessee | Monroe | 75.2 | 74.3 | 76.0 | NaN | NaN | NaN | 878 | 486 | 451 | 520 | NaN | NaN | NaN | 22 | 55 | 35 | 84 | NaN | NaN | NaN | 21 | 6 | 4 | 9 | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 15 | 16 | 16 | 12 | 20 | 29 | 75 | 5910 | 13 | 871 | 2 | 43 | 31 | 73 | 23 | 18 | 29 | 35 | 34 | 36 | 4062 | 16 | 13 | 18 | 437 | 4 | 3 | 6 | 76 | 1321:1 | 15 | 43749 | 39208 | 48290 | 21481 | 34034 | 37748 | NaN | 56 | 23 | 4 | 2 | 7 | 31 | 14 | 9 | 19 | 13198 | 76 | 73 | 78 | 1897 | 11 | 9 | 14 | 46240 | 21.6 | 20.7 | 909 | 2.0 | 287 | 0.6 | 248 | 0.5 | 26 | 0.1 | 2123 | 4.6 | 41988 | 90.8 | 245 | 1 | 0 | 1 | 50.3 | 33868 | 76.1 |
| 64 | 47125 | Tennessee | Montgomery | 76.3 | 75.9 | 76.8 | 75.1 | 85.2 | 76.1 | 2201 | 425 | 407 | 443 | 490 | 206 | 432 | 128 | 61 | 50 | 71 | 65 | NaN | 63 | 141 | 6 | 5 | 7 | 9 | NaN | 6 | 14 | 14 | 15 | 13 | 13 | 14 | 11 | 9 | 13 | 265 | 172 | 27430 | 15 | 21355 | 12 | 101 | 17 | 166 | 13 | 11 | 14 | 41 | 40 | 42 | 13598 | 11 | 10 | 13 | 1910 | 4 | 2 | 5 | 82 | 1213:1 | 6 | 57431 | 53995 | 60867 | 47336 | 52782 | 57723 | NaN | 36 | 32 | 7 | 6 | 8 | 172 | 18 | 15 | 21 | 40631 | 59 | 58 | 60 | 7969 | 12 | 11 | 13 | 200182 | 26.9 | 9.1 | 38930 | 19.4 | 1462 | 0.7 | 4851 | 2.4 | 899 | 0.4 | 20205 | 10.1 | 126915 | 63.4 | 1660 | 1 | 1 | 1 | 50.1 | 34022 | 19.7 |
| 65 | 47127 | Tennessee | Moore | 79.0 | 76.4 | 81.6 | NaN | NaN | NaN | 102 | 383 | 303 | 463 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 12 | 12 | 13 | 13 | 12 | 13 | 15 | 11 | 20 | NaN | NaN | 640 | 10 | 909 | 14 | NaN | NaN | NaN | NaN | NaN | NaN | 34 | 33 | 35 | 409 | 11 | 9 | 13 | 52 | 4 | 3 | 5 | 47 | 2128:1 | NaN | 55448 | 48411 | 62485 | 44028 | NaN | 51535 | NaN | NaN | 33 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2195 | 84 | 82 | 86 | 251 | 10 | 5 | 15 | 6384 | 19.3 | 21.2 | 157 | 2.5 | 21 | 0.3 | 51 | 0.8 | 1 | 0.0 | 130 | 2.0 | 5943 | 93.1 | 0 | 0 | 0 | 1 | 50.1 | 6354 | 99.9 |
| 66 | 47129 | Tennessee | Morgan | 73.5 | 72.1 | 74.8 | NaN | NaN | NaN | 431 | 558 | 503 | 613 | NaN | NaN | NaN | 14 | 82 | 45 | 138 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 13 | 10 | 18 | 21 | 113 | 3250 | 15 | 1753 | 8 | 19 | 29 | 28 | 18 | 12 | 27 | 37 | 36 | 38 | 1651 | 14 | 12 | 17 | 204 | 5 | 3 | 6 | 55 | 1803:1 | NaN | 40667 | 36156 | 45178 | NaN | 24191 | 40772 | NaN | NaN | 57 | 8 | 4 | 14 | 16 | 15 | 8 | 24 | 5994 | 81 | 78 | 84 | 794 | 11 | 8 | 14 | 21636 | 19.5 | 17.4 | 798 | 3.7 | 103 | 0.5 | 62 | 0.3 | 11 | 0.1 | 275 | 1.3 | 20140 | 93.1 | 78 | 0 | 0 | 1 | 45.3 | 21962 | 99.9 |
| 67 | 47131 | Tennessee | Obion | 76.4 | 75.4 | 77.4 | 74.6 | NaN | 76.2 | 534 | 451 | 411 | 492 | 540 | NaN | 453 | 16 | 59 | 34 | 97 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 15 | 16 | 15 | 14 | 15 | 14 | 11 | 18 | 26 | 100 | 5030 | 16 | 1553 | 5 | NaN | NaN | 41 | 19 | 14 | 26 | 36 | 35 | 37 | 2458 | 14 | 12 | 16 | 247 | 4 | 2 | 5 | 135 | 741:1 | 9 | 38160 | 33894 | 42426 | 21760 | 26250 | 41715 | NaN | 54 | 47 | NaN | NaN | NaN | 23 | 15 | 10 | 23 | 8631 | 67 | 66 | 69 | 1450 | 12 | 10 | 14 | 30385 | 21.9 | 20.1 | 3205 | 10.5 | 99 | 0.3 | 133 | 0.4 | 29 | 0.1 | 1316 | 4.3 | 25211 | 83.0 | 238 | 1 | 0 | 1 | 51.6 | 19588 | 61.6 |
| 68 | 47133 | Tennessee | Overton | 74.1 | 72.9 | 75.3 | NaN | NaN | NaN | 472 | 537 | 486 | 588 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 14 | 10 | 18 | 15 | 80 | 2940 | 13 | 98 | 0 | 17 | 26 | 34 | 22 | 15 | 31 | 35 | 33 | 36 | 1915 | 15 | 13 | 18 | 174 | 4 | 2 | 5 | 68 | 1467:1 | NaN | 37154 | 34533 | 39775 | NaN | NaN | NaN | NaN | NaN | 32 | NaN | NaN | NaN | 29 | 26 | 18 | 38 | 7028 | 79 | 77 | 81 | 752 | 9 | 6 | 12 | 22012 | 21.6 | 20.2 | 121 | 0.5 | 85 | 0.4 | 76 | 0.3 | 2 | 0.0 | 312 | 1.4 | 21185 | 96.2 | 43 | 0 | 0 | 1 | 50.7 | 18598 | 84.2 |
| 69 | 47135 | Tennessee | Perry | 72.1 | 70.0 | 74.1 | NaN | NaN | NaN | 209 | 663 | 565 | 760 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 16 | 17 | 16 | 15 | 16 | 14 | 10 | 18 | 8 | 120 | 1260 | 16 | 1018 | 13 | NaN | NaN | 23 | 42 | 26 | 62 | 35 | 33 | 36 | 644 | 15 | 12 | 17 | 78 | 4 | 3 | 6 | 150 | 665:1 | NaN | 37135 | 32246 | 42024 | NaN | NaN | NaN | NaN | 40 | 17 | NaN | NaN | NaN | 11 | 28 | 14 | 50 | 2700 | 82 | 78 | 86 | 368 | 12 | 7 | 17 | 7975 | 21.8 | 21.2 | 188 | 2.4 | 64 | 0.8 | 45 | 0.6 | 1 | 0.0 | 207 | 2.6 | 7312 | 91.7 | 4 | 0 | 0 | 1 | 49.5 | 7915 | 100.0 |
| 70 | 47137 | Tennessee | Pickett | 77.6 | 75.4 | 79.8 | NaN | NaN | NaN | 90 | 385 | 301 | 486 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 15 | 11 | 20 | NaN | NaN | 630 | 13 | 14 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | 34 | 32 | 35 | 361 | 13 | 11 | 15 | 39 | 4 | 3 | 5 | 59 | 1691:1 | NaN | 39858 | 36179 | 43537 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1771 | 81 | 81 | 82 | 85 | 4 | 0 | 9 | 5073 | 18.0 | 27.3 | 8 | 0.2 | 23 | 0.5 | 2 | 0.0 | 4 | 0.1 | 100 | 2.0 | 4893 | 96.5 | 16 | 0 | 0 | 2 | 50.1 | 5077 | 100.0 |
| 71 | 47139 | Tennessee | Polk | 73.7 | 72.3 | 75.1 | NaN | NaN | NaN | 393 | 569 | 510 | 629 | NaN | NaN | NaN | 13 | 96 | 51 | 164 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 16 | 12 | 21 | 11 | 76 | 2140 | 13 | 24 | 0 | 13 | 26 | 30 | 26 | 17 | 37 | 36 | 34 | 37 | 1290 | 13 | 11 | 15 | 151 | 4 | 3 | 6 | 54 | 1862:1 | NaN | 41191 | 37111 | 45271 | NaN | NaN | NaN | NaN | NaN | 27 | NaN | NaN | NaN | 18 | 22 | 13 | 34 | 5355 | 76 | 73 | 79 | 688 | 10 | 8 | 13 | 16757 | 19.8 | 20.7 | 112 | 0.7 | 93 | 0.6 | 49 | 0.3 | 13 | 0.1 | 358 | 2.1 | 15920 | 95.0 | 42 | 0 | 0 | 1 | 50.5 | 16825 | 100.0 |
| 72 | 47141 | Tennessee | Putnam | 75.5 | 74.8 | 76.1 | 79.4 | 83.2 | 75.1 | 1191 | 466 | 438 | 493 | 542 | 217 | 479 | 35 | 55 | 38 | 76 | NaN | NaN | NaN | 39 | 6 | 4 | 9 | NaN | NaN | NaN | 15 | 14 | 15 | 15 | 14 | 15 | 11 | 8 | 13 | 89 | 140 | 11170 | 15 | 6842 | 9 | 41 | 18 | 66 | 13 | 10 | 16 | 33 | 32 | 34 | 6804 | 15 | 13 | 17 | 717 | 4 | 3 | 6 | 193 | 518:1 | 4 | 42437 | 37828 | 47046 | 20274 | 42531 | 38328 | NaN | 44 | 22 | 3 | 2 | 5 | 63 | 17 | 13 | 21 | 18527 | 60 | 59 | 62 | 4562 | 16 | 14 | 18 | 77674 | 21.2 | 16.4 | 1663 | 2.1 | 570 | 0.7 | 1137 | 1.5 | 113 | 0.1 | 4992 | 6.4 | 68562 | 88.3 | 1641 | 2 | 2 | 3 | 50.2 | 25295 | 35.0 |
| 73 | 47143 | Tennessee | Rhea | 73.5 | 72.5 | 74.4 | NaN | NaN | NaN | 665 | 544 | 500 | 587 | NaN | NaN | NaN | 21 | 70 | 44 | 107 | NaN | NaN | NaN | 30 | 11 | 8 | 16 | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 16 | 12 | 20 | 12 | 44 | 5000 | 15 | 1666 | 5 | 18 | 18 | 46 | 20 | 15 | 27 | 35 | 34 | 37 | 2942 | 16 | 14 | 18 | 292 | 4 | 3 | 5 | 73 | 1362:1 | NaN | 43426 | 38137 | 48715 | 31974 | 25139 | 39841 | NaN | 39 | 28 | NaN | NaN | NaN | 32 | 20 | 13 | 28 | 8882 | 70 | 67 | 74 | 1162 | 10 | 7 | 12 | 32691 | 22.7 | 18.5 | 712 | 2.2 | 169 | 0.5 | 176 | 0.5 | 18 | 0.1 | 1645 | 5.0 | 29557 | 90.4 | 381 | 1 | 1 | 2 | 50.5 | 21635 | 68.0 |
| 74 | 47145 | Tennessee | Roane | 75.0 | 74.2 | 75.8 | NaN | NaN | NaN | 1134 | 524 | 491 | 558 | 454 | NaN | 533 | 15 | 37 | 21 | 61 | NaN | NaN | NaN | 23 | 7 | 5 | 11 | NaN | NaN | NaN | 14 | 14 | 14 | 14 | 13 | 14 | 16 | 13 | 21 | 32 | 70 | 6780 | 13 | 5134 | 9 | 69 | 43 | 73 | 20 | 15 | 25 | 35 | 34 | 36 | 3706 | 12 | 10 | 14 | 353 | 3 | 2 | 4 | 89 | 1128:1 | NaN | 48391 | 43598 | 53184 | 33176 | 76446 | 45311 | NaN | 37 | 18 | 3 | 2 | 6 | 49 | 19 | 14 | 25 | 16274 | 75 | 73 | 77 | 2194 | 11 | 9 | 13 | 53036 | 19.0 | 22.5 | 1383 | 2.6 | 238 | 0.4 | 336 | 0.6 | 30 | 0.1 | 1005 | 1.9 | 49198 | 92.8 | 119 | 0 | 0 | 1 | 51.2 | 27628 | 51.0 |
| 75 | 47147 | Tennessee | Robertson | 75.8 | 75.1 | 76.4 | 70.5 | NaN | 76.0 | 1060 | 435 | 408 | 462 | 675 | NaN | 425 | 43 | 63 | 46 | 85 | NaN | NaN | NaN | 38 | 6 | 4 | 8 | NaN | NaN | NaN | 12 | 12 | 13 | 13 | 12 | 13 | 12 | 9 | 15 | 92 | 163 | 6880 | 10 | 1073 | 2 | 41 | 20 | 92 | 19 | 16 | 24 | 35 | 34 | 36 | 5571 | 13 | 11 | 15 | 674 | 4 | 3 | 5 | 87 | 1150:1 | 9 | 59771 | 55589 | 63953 | 33750 | 51574 | 60004 | NaN | 56 | 43 | 6 | 4 | 9 | 51 | 15 | 11 | 20 | 18748 | 75 | 73 | 77 | 2603 | 11 | 9 | 12 | 70177 | 24.3 | 14.4 | 5117 | 7.3 | 404 | 0.6 | 470 | 0.7 | 71 | 0.1 | 4890 | 7.0 | 58539 | 83.4 | 899 | 1 | 1 | 2 | 50.7 | 35289 | 53.2 |
| 76 | 47149 | Tennessee | Rutherford | 77.9 | 77.5 | 78.2 | 77.3 | 93.5 | 77.7 | 3244 | 366 | 353 | 378 | 389 | 207 | 375 | 158 | 52 | 44 | 61 | 74 | 53 | 44 | 153 | 6 | 5 | 7 | 7 | NaN | 6 | 12 | 12 | 13 | 12 | 12 | 12 | 11 | 9 | 14 | 437 | 179 | 34810 | 12 | 20893 | 8 | 177 | 19 | 220 | 11 | 9 | 12 | 37 | 36 | 38 | 21730 | 11 | 10 | 12 | 2634 | 3 | 2 | 4 | 97 | 1026:1 | 4 | 68082 | 64886 | 71278 | 48464 | 45381 | 66001 | NaN | 33 | 28 | 4 | 3 | 5 | 153 | 10 | 9 | 12 | 69934 | 66 | 65 | 67 | 11847 | 11 | 10 | 12 | 317157 | 24.7 | 10.1 | 47505 | 15.0 | 1784 | 0.6 | 11175 | 3.5 | 354 | 0.1 | 25494 | 8.0 | 224712 | 70.9 | 6209 | 2 | 2 | 3 | 50.7 | 44699 | 17.0 |
| 77 | 47151 | Tennessee | Scott | 72.2 | 70.9 | 73.4 | NaN | NaN | NaN | 467 | 609 | 552 | 666 | NaN | NaN | NaN | 18 | 84 | 50 | 132 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 16 | 16 | 17 | 16 | 15 | 16 | 12 | 9 | 17 | 7 | 39 | 3800 | 17 | 382 | 2 | 13 | 20 | 29 | 19 | 13 | 27 | 35 | 33 | 36 | 1840 | 14 | 12 | 17 | 192 | 4 | 2 | 5 | 105 | 956:1 | NaN | 34828 | 30720 | 38936 | NaN | 20625 | 32460 | NaN | NaN | 35 | NaN | NaN | NaN | 30 | 27 | 18 | 39 | 5941 | 70 | 67 | 73 | 1073 | 13 | 10 | 17 | 21989 | 24.4 | 16.4 | 44 | 0.2 | 68 | 0.3 | 53 | 0.2 | 4 | 0.0 | 203 | 0.9 | 21401 | 97.3 | 17 | 0 | 0 | 1 | 50.7 | 17906 | 80.6 |
| 78 | 47153 | Tennessee | Sequatchie | 76.9 | 75.4 | 78.4 | NaN | NaN | NaN | 252 | 418 | 363 | 473 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 14 | 10 | 18 | 6 | 48 | 1800 | 12 | 3 | 0 | NaN | NaN | 12 | 12 | 6 | 20 | 35 | 33 | 36 | 1120 | 13 | 11 | 15 | 114 | 3 | 2 | 5 | 81 | 1228:1 | NaN | 45100 | 39345 | 50855 | NaN | 58750 | 50772 | NaN | NaN | 9 | NaN | NaN | NaN | 11 | 15 | 7 | 27 | 4153 | 75 | 71 | 80 | 459 | 9 | 6 | 12 | 14736 | 21.1 | 19.9 | 83 | 0.6 | 99 | 0.7 | 69 | 0.5 | 11 | 0.1 | 537 | 3.6 | 13779 | 93.5 | 56 | 0 | 0 | 1 | 50.6 | 10415 | 73.8 |
| 79 | 47155 | Tennessee | Sevier | 76.3 | 75.7 | 76.8 | NaN | 87.4 | 75.9 | 1638 | 437 | 415 | 460 | NaN | 251 | 452 | 33 | 41 | 28 | 57 | NaN | NaN | NaN | 41 | 6 | 4 | 8 | NaN | NaN | NaN | 14 | 14 | 14 | 14 | 13 | 14 | 15 | 11 | 19 | 63 | 77 | 11300 | 12 | 4885 | 5 | 85 | 29 | 119 | 18 | 15 | 21 | 35 | 33 | 36 | 11021 | 19 | 17 | 21 | 966 | 5 | 3 | 6 | 112 | 896:1 | 5 | 48482 | 45130 | 51834 | 44080 | 32334 | 45486 | NaN | 64 | 22 | NaN | NaN | NaN | 66 | 14 | 11 | 18 | 24861 | 67 | 66 | 69 | 4133 | 12 | 10 | 13 | 97638 | 20.8 | 19.2 | 1084 | 1.1 | 595 | 0.6 | 1315 | 1.3 | 43 | 0.0 | 5876 | 6.0 | 87817 | 89.9 | 1819 | 2 | 2 | 3 | 51.0 | 50920 | 56.6 |
| 80 | 47157 | Tennessee | Shelby | 75.8 | 75.6 | 76.0 | 73.5 | 91.9 | 78.0 | 13893 | 465 | 458 | 473 | 572 | 223 | 374 | 753 | 79 | 74 | 85 | 102 | 48 | 46 | 912 | 10 | 9 | 10 | 13 | 4 | 5 | 14 | 14 | 14 | 14 | 14 | 14 | 12 | 11 | 14 | 5731 | 750 | 198610 | 21 | 104909 | 11 | 600 | 21 | 838 | 13 | 12 | 14 | 38 | 38 | 39 | 84327 | 15 | 14 | 16 | 8925 | 4 | 3 | 5 | 122 | 820:1 | 11 | 49563 | 47605 | 51521 | 35061 | 36912 | 72343 | NaN | 65 | 61 | 19 | 18 | 20 | 1107 | 24 | 22 | 25 | 195204 | 56 | 55 | 56 | 60300 | 18 | 17 | 19 | 936961 | 25.0 | 13.1 | 502118 | 53.6 | 2988 | 0.3 | 25194 | 2.7 | 739 | 0.1 | 59571 | 6.4 | 335966 | 35.9 | 17727 | 2 | 2 | 2 | 52.4 | 25601 | 2.8 |
| 81 | 47159 | Tennessee | Smith | 76.4 | 75.2 | 77.6 | NaN | NaN | NaN | 321 | 447 | 396 | 498 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 14 | 11 | 19 | 18 | 112 | 2330 | 12 | 110 | 1 | 22 | 38 | 33 | 24 | 17 | 34 | 33 | 32 | 35 | 1498 | 13 | 11 | 15 | 184 | 4 | 3 | 5 | 51 | 1964:1 | NaN | 47653 | 41674 | 53632 | 21797 | 46500 | 45023 | NaN | 42 | 23 | NaN | NaN | NaN | 13 | 14 | 7 | 23 | 5633 | 75 | 72 | 77 | 712 | 10 | 7 | 13 | 19636 | 23.0 | 16.6 | 429 | 2.2 | 95 | 0.5 | 73 | 0.4 | 3 | 0.0 | 523 | 2.7 | 18272 | 93.1 | 16 | 0 | 0 | 1 | 50.3 | 15884 | 82.9 |
| 82 | 47161 | Tennessee | Stewart | 75.7 | 74.0 | 77.4 | NaN | NaN | NaN | 240 | 452 | 391 | 513 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 13 | 14 | 13 | 13 | 14 | 15 | 11 | 20 | 8 | 71 | 1840 | 14 | 97 | 1 | NaN | NaN | 18 | 19 | 12 | 31 | 35 | 34 | 36 | 1051 | 13 | 11 | 16 | 139 | 5 | 3 | 7 | 82 | 1214:1 | NaN | 48175 | 42038 | 54312 | 32448 | NaN | 45066 | NaN | 26 | 21 | NaN | NaN | NaN | 20 | 30 | 18 | 47 | 3769 | 71 | 67 | 75 | 603 | 12 | 8 | 16 | 13355 | 20.8 | 19.9 | 223 | 1.7 | 100 | 0.7 | 139 | 1.0 | 7 | 0.1 | 379 | 2.8 | 12279 | 91.9 | 23 | 0 | 0 | 1 | 50.0 | 13324 | 100.0 |
| 83 | 47163 | Tennessee | Sullivan | 75.8 | 75.4 | 76.2 | 73.7 | 103.7 | 75.7 | 2934 | 471 | 453 | 489 | 628 | NaN | 475 | 53 | 43 | 32 | 56 | NaN | NaN | NaN | 65 | 6 | 5 | 8 | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 14 | 15 | 15 | 13 | 17 | 121 | 90 | 20220 | 13 | 20210 | 13 | 120 | 25 | 156 | 14 | 12 | 16 | 35 | 34 | 36 | 11261 | 12 | 11 | 14 | 908 | 3 | 2 | 4 | 183 | 546:1 | 8 | 45224 | 41766 | 48682 | 30486 | 25714 | 42876 | NaN | 54 | 35 | 3 | 2 | 4 | 112 | 14 | 12 | 17 | 48178 | 73 | 71 | 74 | 6306 | 10 | 9 | 11 | 157158 | 19.5 | 21.5 | 3423 | 2.2 | 566 | 0.4 | 1212 | 0.8 | 67 | 0.0 | 2936 | 1.9 | 146947 | 93.5 | 586 | 0 | 0 | 1 | 51.4 | 40086 | 25.6 |
| 84 | 47165 | Tennessee | Sumner | 78.0 | 77.6 | 78.4 | 77.5 | 88.0 | 77.7 | 2320 | 363 | 348 | 378 | 410 | 163 | 369 | 74 | 43 | 34 | 54 | NaN | NaN | NaN | 81 | 6 | 5 | 7 | NaN | NaN | NaN | 12 | 12 | 12 | 12 | 12 | 13 | 11 | 9 | 14 | 180 | 123 | 17550 | 10 | 11149 | 7 | 103 | 19 | 152 | 13 | 11 | 15 | 33 | 32 | 34 | 11950 | 11 | 10 | 12 | 1448 | 3 | 2 | 4 | 89 | 1119:1 | 6 | 65174 | 62008 | 68340 | 54928 | 39959 | 62483 | NaN | 45 | 38 | 4 | 3 | 5 | 142 | 16 | 14 | 19 | 47485 | 74 | 72 | 75 | 6688 | 11 | 10 | 12 | 183545 | 23.8 | 15.4 | 13623 | 7.4 | 706 | 0.4 | 2599 | 1.4 | 191 | 0.1 | 9034 | 4.9 | 154733 | 84.3 | 1495 | 1 | 1 | 1 | 51.1 | 44792 | 27.9 |
| 85 | 47167 | Tennessee | Tipton | 74.7 | 74.0 | 75.4 | 73.3 | NaN | 74.7 | 1005 | 484 | 453 | 514 | 539 | NaN | 485 | 32 | 52 | 35 | 73 | 92 | NaN | 43 | 30 | 6 | 4 | 8 | NaN | NaN | NaN | 14 | 13 | 14 | 13 | 13 | 13 | 15 | 12 | 18 | 81 | 160 | 8770 | 14 | 3742 | 6 | 49 | 27 | 81 | 19 | 15 | 23 | 37 | 36 | 38 | 4732 | 13 | 11 | 15 | 480 | 3 | 2 | 4 | 70 | 1427:1 | 10 | 56511 | 50916 | 62106 | 32392 | 74095 | 61702 | NaN | 41 | 35 | 6 | 4 | 9 | 54 | 18 | 13 | 23 | 14831 | 69 | 67 | 72 | 2133 | 10 | 8 | 12 | 61366 | 24.9 | 14.1 | 11263 | 18.4 | 293 | 0.5 | 466 | 0.8 | 97 | 0.2 | 1730 | 2.8 | 46492 | 75.8 | 391 | 1 | 0 | 1 | 50.7 | 33671 | 55.1 |
| 86 | 47169 | Tennessee | Trousdale | 74.1 | 72.3 | 75.8 | NaN | NaN | NaN | 153 | 499 | 418 | 580 | 658 | NaN | 495 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 13 | 13 | 14 | 13 | 13 | 14 | 14 | 10 | 19 | 15 | 223 | 1010 | 13 | NaN | NaN | NaN | NaN | 16 | 28 | 16 | 45 | 35 | 34 | 36 | 769 | 15 | 13 | 18 | 86 | 4 | 3 | 6 | 99 | 1008:1 | NaN | 49711 | 45455 | 53967 | 27102 | NaN | 49023 | NaN | 58 | 57 | NaN | NaN | NaN | 10 | 24 | 11 | 44 | 2101 | 71 | 65 | 78 | 398 | 14 | 8 | 21 | 10083 | 19.1 | 13.8 | 1066 | 10.6 | 69 | 0.7 | 56 | 0.6 | 1 | 0.0 | 266 | 2.6 | 8481 | 84.1 | 52 | 1 | 0 | 2 | 43.5 | 7870 | 100.0 |
| 87 | 47171 | Tennessee | Unicoi | 74.4 | 73.0 | 75.7 | NaN | NaN | NaN | 392 | 531 | 474 | 587 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 15 | 14 | 15 | 15 | 11 | 19 | 15 | 97 | 2580 | 14 | 1124 | 6 | 20 | 37 | 23 | 18 | 12 | 27 | 35 | 34 | 36 | 1465 | 14 | 12 | 16 | 130 | 4 | 2 | 5 | 56 | 1776:1 | NaN | 41188 | 36627 | 45749 | NaN | NaN | NaN | NaN | NaN | 16 | 8 | 4 | 15 | 21 | 24 | 15 | 36 | 5513 | 72 | 69 | 76 | 803 | 11 | 8 | 15 | 17759 | 18.8 | 22.9 | 74 | 0.4 | 73 | 0.4 | 45 | 0.3 | 8 | 0.0 | 854 | 4.8 | 16557 | 93.2 | 211 | 1 | 0 | 2 | 50.8 | 8180 | 44.7 |
| 88 | 47173 | Tennessee | Union | 74.1 | 72.8 | 75.5 | NaN | NaN | NaN | 388 | 542 | 485 | 599 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 16 | 11 | 21 | NaN | NaN | 2760 | 15 | 139 | 1 | 26 | 45 | 26 | 19 | 13 | 28 | 35 | 34 | 36 | 1781 | 16 | 13 | 18 | 190 | 4 | 3 | 6 | 51 | 1944:1 | NaN | 40357 | 35994 | 44720 | NaN | NaN | NaN | NaN | NaN | 19 | 8 | 4 | 15 | 26 | 27 | 18 | 40 | 5492 | 76 | 72 | 79 | 638 | 9 | 6 | 12 | 19442 | 22.0 | 18.0 | 56 | 0.3 | 88 | 0.5 | 41 | 0.2 | 16 | 0.1 | 315 | 1.6 | 18736 | 96.4 | 26 | 0 | 0 | 1 | 50.6 | 19109 | 100.0 |
| 89 | 47175 | Tennessee | Van buren | 73.4 | 70.9 | 76.0 | NaN | NaN | NaN | 133 | 548 | 445 | 651 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 14 | 10 | 19 | NaN | NaN | 700 | 13 | 20 | 0 | NaN | NaN | 11 | 28 | 14 | 50 | 34 | 33 | 36 | 465 | 14 | 12 | 17 | 48 | 4 | 3 | 6 | 35 | 2871:1 | NaN | 38478 | 33509 | 43447 | NaN | NaN | NaN | NaN | NaN | 13 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1888 | 88 | 87 | 88 | 192 | 9 | 5 | 14 | 5742 | 19.4 | 23.2 | 43 | 0.7 | 22 | 0.4 | 12 | 0.2 | 1 | 0.0 | 88 | 1.5 | 5506 | 95.9 | 0 | 0 | 0 | 2 | 49.6 | 5548 | 100.0 |
| 90 | 47177 | Tennessee | Warren | 74.4 | 73.5 | 75.2 | NaN | 79.4 | 74.1 | 781 | 526 | 487 | 564 | 642 | NaN | 540 | 22 | 57 | 36 | 87 | NaN | NaN | NaN | 27 | 8 | 6 | 12 | NaN | NaN | NaN | 15 | 15 | 16 | 15 | 14 | 15 | 17 | 13 | 21 | 31 | 93 | 5140 | 13 | 1607 | 4 | 21 | 17 | 87 | 31 | 25 | 38 | 34 | 33 | 35 | 4082 | 17 | 15 | 20 | 441 | 4 | 3 | 6 | 101 | 991:1 | 11 | 37692 | 34361 | 41023 | 25990 | 37145 | 37251 | NaN | 29 | 19 | 5 | 3 | 8 | 37 | 18 | 13 | 25 | 10794 | 69 | 66 | 71 | 1582 | 11 | 9 | 13 | 40651 | 23.7 | 17.4 | 1308 | 3.2 | 203 | 0.5 | 318 | 0.8 | 36 | 0.1 | 3707 | 9.1 | 34637 | 85.2 | 835 | 2 | 1 | 3 | 50.7 | 24453 | 61.4 |
| 91 | 47179 | Tennessee | Washington | 76.0 | 75.5 | 76.4 | 71.9 | 95.0 | 75.9 | 2107 | 453 | 433 | 474 | 694 | 283 | 451 | 72 | 73 | 57 | 92 | NaN | NaN | NaN | 84 | 9 | 7 | 11 | NaN | NaN | NaN | 14 | 13 | 14 | 14 | 13 | 14 | 14 | 12 | 17 | 186 | 171 | 16860 | 13 | 9478 | 8 | 100 | 26 | 78 | 9 | 7 | 11 | 38 | 37 | 39 | 9218 | 12 | 10 | 14 | 822 | 3 | 2 | 4 | 293 | 341:1 | 4 | 43194 | 39392 | 46996 | 29529 | 30500 | 45091 | NaN | 50 | 37 | 3 | 2 | 4 | 76 | 12 | 10 | 15 | 34063 | 65 | 63 | 66 | 5974 | 12 | 10 | 13 | 127806 | 19.2 | 17.9 | 5365 | 4.2 | 554 | 0.4 | 1982 | 1.6 | 75 | 0.1 | 4412 | 3.5 | 113428 | 88.8 | 312 | 0 | 0 | 0 | 51.1 | 32493 | 26.4 |
| 92 | 47181 | Tennessee | Wayne | 75.6 | 74.3 | 76.9 | NaN | NaN | NaN | 335 | 509 | 452 | 566 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 15 | 16 | 14 | 14 | 15 | 14 | 11 | 19 | 14 | 95 | 2330 | 14 | 1556 | 9 | NaN | NaN | 21 | 18 | 11 | 27 | 38 | 36 | 39 | 1271 | 15 | 12 | 17 | 145 | 5 | 3 | 7 | 90 | 1106:1 | 17 | 36612 | 32025 | 41199 | 40096 | 41313 | 34696 | NaN | NaN | 32 | NaN | NaN | NaN | 12 | 14 | 7 | 25 | 4715 | 80 | 77 | 84 | 586 | 11 | 8 | 14 | 16583 | 17.3 | 19.1 | 1051 | 6.3 | 64 | 0.4 | 50 | 0.3 | 5 | 0.0 | 345 | 2.1 | 14925 | 90.0 | 28 | 0 | 0 | 1 | 44.9 | 17021 | 100.0 |
| 93 | 47183 | Tennessee | Weakley | 75.7 | 74.6 | 76.7 | 73.5 | NaN | 75.7 | 550 | 470 | 429 | 511 | 530 | NaN | 467 | 19 | 72 | 43 | 113 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 14 | 14 | 15 | 14 | 14 | 15 | 12 | 9 | 15 | 16 | 55 | 5160 | 15 | 2517 | 7 | 15 | 15 | 40 | 17 | 12 | 23 | 35 | 34 | 36 | 2293 | 12 | 10 | 14 | 232 | 3 | 2 | 5 | 93 | 1075:1 | NaN | 39424 | 34790 | 44058 | 19965 | 31250 | 38270 | NaN | 49 | 46 | 6 | 3 | 10 | 36 | 21 | 15 | 29 | 9060 | 67 | 65 | 69 | 1401 | 11 | 9 | 13 | 33337 | 19.5 | 18.3 | 2538 | 7.6 | 136 | 0.4 | 394 | 1.2 | 14 | 0.0 | 817 | 2.5 | 29030 | 87.1 | 131 | 0 | 0 | 1 | 51.1 | 23466 | 67.0 |
| 94 | 47185 | Tennessee | White | 74.2 | 73.2 | 75.3 | NaN | NaN | NaN | 553 | 539 | 491 | 586 | NaN | NaN | NaN | 13 | 56 | 30 | 95 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 15 | 14 | 15 | 14 | 14 | 15 | 15 | 11 | 20 | 22 | 99 | 3350 | 13 | 1409 | 5 | 21 | 26 | 47 | 25 | 19 | 34 | 34 | 33 | 35 | 2140 | 14 | 12 | 16 | 201 | 3 | 2 | 5 | 71 | 1408:1 | NaN | 39642 | 34857 | 44427 | 30779 | 30781 | 38331 | NaN | 62 | 47 | NaN | NaN | NaN | 29 | 22 | 15 | 31 | 7673 | 78 | 76 | 81 | 942 | 10 | 7 | 13 | 26753 | 21.8 | 20.1 | 460 | 1.7 | 134 | 0.5 | 102 | 0.4 | 24 | 0.1 | 686 | 2.6 | 25005 | 93.5 | 80 | 0 | 0 | 1 | 51.1 | 20201 | 78.2 |
| 95 | 47187 | Tennessee | Williamson | 82.1 | 81.7 | 82.5 | 80.2 | 87.2 | 81.9 | 1475 | 206 | 196 | 217 | 299 | 178 | 208 | 59 | 25 | 19 | 32 | NaN | NaN | NaN | 54 | 4 | 3 | 5 | NaN | NaN | NaN | 10 | 10 | 10 | 11 | 10 | 11 | 10 | 8 | 13 | 137 | 80 | 14450 | 7 | 6068 | 3 | 81 | 12 | 99 | 7 | 6 | 8 | 33 | 32 | 34 | 9314 | 7 | 6 | 8 | 1864 | 3 | 2 | 4 | 110 | 905:1 | 3 | 111427 | 102231 | 120623 | 70818 | 69550 | 105715 | NaN | 30 | 30 | 1 | 1 | 2 | 95 | 9 | 7 | 11 | 58932 | 81 | 80 | 81 | 6192 | 9 | 8 | 10 | 226257 | 27.5 | 12.8 | 9783 | 4.3 | 601 | 0.3 | 10012 | 4.4 | 132 | 0.1 | 10857 | 4.8 | 191775 | 84.8 | 1459 | 1 | 1 | 1 | 51.1 | 35512 | 19.4 |
| 96 | 47189 | Tennessee | Wilson | 78.4 | 77.9 | 78.9 | 75.4 | 98.8 | 78.4 | 1664 | 347 | 330 | 365 | 443 | 187 | 345 | 61 | 49 | 37 | 62 | 112 | NaN | 43 | 45 | 5 | 3 | 6 | NaN | NaN | NaN | 11 | 11 | 11 | 12 | 11 | 12 | 13 | 10 | 16 | 134 | 125 | 12130 | 10 | 4430 | 4 | 105 | 26 | 110 | 12 | 10 | 15 | 33 | 32 | 34 | 7603 | 9 | 8 | 11 | 1009 | 3 | 2 | 4 | 111 | 898:1 | 5 | 70674 | 65885 | 75463 | 51448 | 58148 | 67758 | NaN | 32 | 25 | 3 | 2 | 5 | 83 | 13 | 10 | 16 | 36338 | 77 | 75 | 79 | 4861 | 11 | 9 | 12 | 136442 | 23.9 | 15.4 | 9388 | 6.9 | 685 | 0.5 | 2225 | 1.6 | 126 | 0.1 | 5757 | 4.2 | 116243 | 85.2 | 924 | 1 | 0 | 1 | 50.9 | 43850 | 38.5 |
sns.pairplot((abs_health_3.dropna()))
<seaborn.axisgrid.PairGrid at 0x2733f647748>
more_disp = more_disp.drop('County',axis=1)
--------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-178-15cbee0a744b> in <module>() ----> 1 more_disp = more_disp.drop('County',axis=1) ~\Anaconda3\lib\site-packages\pandas\core\frame.py in drop(self, labels, axis, index, columns, level, inplace, errors) 3692 index=index, columns=columns, 3693 level=level, inplace=inplace, -> 3694 errors=errors) 3695 3696 @rewrite_axis_style_signature('mapper', [('copy', True), ~\Anaconda3\lib\site-packages\pandas\core\generic.py in drop(self, labels, axis, index, columns, level, inplace, errors) 3106 for axis, labels in axes.items(): 3107 if labels is not None: -> 3108 obj = obj._drop_axis(labels, axis, level=level, errors=errors) 3109 3110 if inplace: ~\Anaconda3\lib\site-packages\pandas\core\generic.py in _drop_axis(self, labels, axis, level, errors) 3138 new_axis = axis.drop(labels, level=level, errors=errors) 3139 else: -> 3140 new_axis = axis.drop(labels, errors=errors) 3141 dropped = self.reindex(**{axis_name: new_axis}) 3142 try: ~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in drop(self, labels, errors) 4385 if errors != 'ignore': 4386 raise KeyError( -> 4387 'labels %s not contained in axis' % labels[mask]) 4388 indexer = indexer[~mask] 4389 return self.delete(indexer) KeyError: "labels ['County'] not contained in axis"
more_dispa = more_disp.iloc[:,1:].astype(float)
more_dispa['County'] = more_disp['NAME10']
more_dispa = more_dispa.drop('%Children eligible for free or reduced price lunch', axis = 1)
corr = more_dispa.corr()
# plot the heatmap
sns.heatmap(corr)
<matplotlib.axes._subplots.AxesSubplot at 0x2736d7fdf60>
more_disp.shape
(95, 36)
abs_health3.shape
(95, 186)
from sklearn.linear_model import LinearRegression
from sklearn.utils import resample
from sklearn.metrics import confusion_matrix, classification_report, accuracy_score
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import RandomForestRegressor
from sklearn.cross_validation import train_test_split
more_dispa.shape
(95, 35)
p1 = more_dispa.iloc[:,3:35]
p2 = abs_health_3a.iloc[:, 4:]#change to 4?
prep = pd.merge(p1,p2, on = 'County')
X = prep.drop(['County','Child mortality # Deaths','Infant mortality # of Deaths', 'HIV prevalence # of cases',
'# of Food insecure', '# with Limited access to healthy foods', '# of Drug overdose deaths', '# of Uninsured adults',
'# of Uninsured children','# of Homeowners'],axis = 1)
X.shape
(95, 39)
y = abs_health_3a.iloc[:,0]
X=X.fillna(X.mean())
X.info()
<class 'pandas.core.frame.DataFrame'> Int64Index: 95 entries, 0 to 94 Data columns (total 39 columns): classroom_teacher 95 non-null float64 principal 95 non-null float64 Life expectancy 95 non-null float64 Premature age-adjusted mortality 95 non-null float64 Child Mortality Rate 95 non-null float64 Infant Mortality Rate 95 non-null float64 % Frequent physical distress 95 non-null float64 %Frequent mental distress 95 non-null float64 % Diabetes prevalence 95 non-null float64 HIV Prevalence Rate 95 non-null float64 % of Food Insecure 95 non-null float64 % of limited access to healthy foods 95 non-null float64 Drug Overdose Mortality Rate 95 non-null float64 % Insufficient sleep 95 non-null float64 % of Uninsured Adults 95 non-null float64 % of Uninsured children 95 non-null float64 Median household income 95 non-null float64 Homicides 95 non-null float64 # of Firearm fatalities 95 non-null float64 % of Homeowners 95 non-null float64 # of Households with Severe housing cost burden 95 non-null float64 % of Severe Housing Cost Burden 95 non-null float64 Poor mental health days 95 non-null float64 % Low Birth Weight 95 non-null float64 Adult smoking 95 non-null float64 Adult obesity 95 non-null float64 Food environment index 95 non-null float64 Physical inactivity 95 non-null float64 Teen births 95 non-null float64 % Uninsured 95 non-null float64 Primary care physicians 95 non-null float64 Dentists 95 non-null float64 Mental health providers 95 non-null float64 Flu vaccinations 95 non-null float64 % Unemployed 95 non-null float64 Children in poverty 95 non-null float64 % Single-Parent Household 95 non-null float64 Violent crime 95 non-null float64 Severe housing problems 95 non-null float64 dtypes: float64(39) memory usage: 29.7 KB
Xtrain, Xtest,ytrain, ytest = train_test_split(X,y,test_size = 0.25, random_state=42)
linear_model = LinearRegression()
linear_model.fit(Xtrain, ytrain)
linear_predict = tn_ab_model.predict(Xtest)
linear_model.coef_[0]
3.1653027140779854e-06
linear_model.intercept_
0.49259947327922404
y_try=np.array(ytest)
df=pd.DataFrame(y_try,linear_predict).reset_index()
df.columns=('Linear_predict','y_actual')
df[['y_actual','Linear_predict']].plot(alpha=0.5)
[Text(140.375,0.5,'help')]
params = pd.Series(linear_model.coef_,index=X.columns)
np.random.seed(1)
err = np.std([linear_model.fit(*resample(X,y)).coef_
for i in range(1000)],0)
print(pd.DataFrame({'effect':params,
'error': err}))
effect error classroom_teacher 3.165303e-06 0.000006 principal 1.097783e-06 0.000002 Life expectancy 1.587947e-03 0.011374 Premature age-adjusted mortality -4.089742e-05 0.000088 Child Mortality Rate -8.587819e-04 0.001218 Infant Mortality Rate 1.582024e-02 0.011118 % Frequent physical distress -2.587153e-02 0.025625 %Frequent mental distress -2.770411e-02 0.024326 % Diabetes prevalence -4.987517e-03 0.009763 HIV Prevalence Rate 1.735406e-05 0.000178 % of Food Insecure -1.979509e-02 0.030013 % of limited access to healthy foods -9.873472e-03 0.018790 Drug Overdose Mortality Rate 1.429169e-03 0.001275 % Insufficient sleep -2.945012e-03 0.008342 % of Uninsured Adults 3.867257e-03 0.022186 % of Uninsured children 6.003258e-03 0.028345 Median household income 2.813301e-07 0.000003 Homicides -5.845238e-03 0.008310 # of Firearm fatalities 7.078335e-04 0.001076 % of Homeowners 7.483313e-04 0.003311 # of Households with Severe housing cost burden -3.432733e-06 0.000038 % of Severe Housing Cost Burden 2.366836e-03 0.010130 Poor mental health days 1.533780e-01 0.130880 % Low Birth Weight 2.012967e-03 0.012526 Adult smoking 6.354654e-03 0.008389 Adult obesity 8.538415e-03 0.005825 Food environment index -1.091789e-01 0.193318 Physical inactivity -8.819751e-03 0.004175 Teen births -7.969505e-04 0.001959 % Uninsured 1.351271e-04 0.029050 Primary care physicians 7.059433e-04 0.000658 Dentists -1.890640e-03 0.001358 Mental health providers -1.195661e-04 0.000267 Flu vaccinations 2.776199e-03 0.002465 % Unemployed 1.795528e-02 0.022178 Children in poverty 5.978580e-03 0.004665 % Single-Parent Household -1.179948e-03 0.002816 Violent crime 1.400402e-04 0.000123 Severe housing problems -3.034072e-04 0.008896
param_error = pd.DataFrame({'effect':params,
'error': err})
param_error.sort_values(by='effect', ascending = False)
| effect | error | |
|---|---|---|
| Poor mental health days | 1.533780e-01 | 0.130880 |
| % Unemployed | 1.795528e-02 | 0.022178 |
| Infant Mortality Rate | 1.582024e-02 | 0.011118 |
| Adult obesity | 8.538415e-03 | 0.005825 |
| Adult smoking | 6.354654e-03 | 0.008389 |
| % of Uninsured children | 6.003258e-03 | 0.028345 |
| Children in poverty | 5.978580e-03 | 0.004665 |
| % of Uninsured Adults | 3.867257e-03 | 0.022186 |
| Flu vaccinations | 2.776199e-03 | 0.002465 |
| % of Severe Housing Cost Burden | 2.366836e-03 | 0.010130 |
| % Low Birth Weight | 2.012967e-03 | 0.012526 |
| Life expectancy | 1.587947e-03 | 0.011374 |
| Drug Overdose Mortality Rate | 1.429169e-03 | 0.001275 |
| % of Homeowners | 7.483313e-04 | 0.003311 |
| # of Firearm fatalities | 7.078335e-04 | 0.001076 |
| Primary care physicians | 7.059433e-04 | 0.000658 |
| Violent crime | 1.400402e-04 | 0.000123 |
| % Uninsured | 1.351271e-04 | 0.029050 |
| HIV Prevalence Rate | 1.735406e-05 | 0.000178 |
| classroom_teacher | 3.165303e-06 | 0.000006 |
| principal | 1.097783e-06 | 0.000002 |
| Median household income | 2.813301e-07 | 0.000003 |
| # of Households with Severe housing cost burden | -3.432733e-06 | 0.000038 |
| Premature age-adjusted mortality | -4.089742e-05 | 0.000088 |
| Mental health providers | -1.195661e-04 | 0.000267 |
| Severe housing problems | -3.034072e-04 | 0.008896 |
| Teen births | -7.969505e-04 | 0.001959 |
| Child Mortality Rate | -8.587819e-04 | 0.001218 |
| % Single-Parent Household | -1.179948e-03 | 0.002816 |
| Dentists | -1.890640e-03 | 0.001358 |
| % Insufficient sleep | -2.945012e-03 | 0.008342 |
| % Diabetes prevalence | -4.987517e-03 | 0.009763 |
| Homicides | -5.845238e-03 | 0.008310 |
| Physical inactivity | -8.819751e-03 | 0.004175 |
| % of limited access to healthy foods | -9.873472e-03 | 0.018790 |
| % of Food Insecure | -1.979509e-02 | 0.030013 |
| % Frequent physical distress | -2.587153e-02 | 0.025625 |
| %Frequent mental distress | -2.770411e-02 | 0.024326 |
| Food environment index | -1.091789e-01 | 0.193318 |
forest = RandomForestRegressor()
forest.fit(Xtrain,ytrain)
RF_model = forest.predict(Xtest)
df['RF model'] = RF_model
df[['ytest','Linear model','RF model']].plot(alpha=0.5)
plt.xlabel = 'Observations'
plt.ylabel = 'Percentage of Chronically Absent'
plt.show()
from sklearn.metrics import mean_squared_error, mean_absolute_error
from math import sqrt
MSE_linear = mean_squared_error(ytest,linear_predict)
MSE_rf = mean_squared_error(ytest, RF_model)
rms_linear = sqrt(mean_squared_error(ytest, linear_predict)) #May not be ideal because of outlier
rms_rf = sqrt(mean_squared_error(ytest,RF_model))
MAE_linear = mean_absolute_error(ytest,linear_predict)
MAE_rf = mean_absolute_error(ytest,RF_model)
print('The mean square error (MSE) for the linear model was', MSE_linear)
print('The mean square error (MSE) for the random forest model was', MSE_rf)
print('The root mean square error (RMSE) for the linear model was', rms_linear)
print('The root mean square error (RMSE) for the random forest model was', rms_rf)
print('The mean absolute error (MAE) for the linear model was', MAE_linear)
print('The mean absolute error (MAE) for the random forest model was', MAE_rf)
The mean square error (MSE) for the linear model was 0.004449960491814895 The mean square error (MSE) for the random forest model was 0.003920884483173963 The root mean square error (RMSE) for the linear model was 0.06670802419360729 The root mean square error (RMSE) for the random forest model was 0.06261696641625146 The mean absolute error (MAE) for the linear model was 0.04804978027775752 The mean absolute error (MAE) for the random forest model was 0.04440538858088191